instruction
stringclasses 45
values | integer
sequencelengths 168
1.03k
| output
dict |
|---|---|---|
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
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],
[
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]
]
},
"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
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],
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],
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]
]
}
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 423.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
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157,
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"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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"3. Local Minima": {
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 469.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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[
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]
},
"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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}
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 586.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 399.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
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350,
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"3. Local Minima": null
} |
Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 401.",
"2. Local Maxima": null,
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 338.",
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"3. Local Minima": null
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Symmetry represents the body is divided into left and right sides, and the similarity between the symmetrical joints is calculated. Near the maximum value, the less symmetry there is between the left and right sides of the body with moving only one side of arm or leg, and near the minimum value, the more symmetry there is between the left and right sides of the body.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 525.",
"2. Local Maxima": null,
"3. Local Minima": null
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"3. Local Minima": null
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 396.",
"2. Local Maxima": null,
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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"2. Local Maxima": null,
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To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 296.",
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 400.",
"2. Local Maxima": null,
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"3. Local Minima": null
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 513.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
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"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
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To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 432.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
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},
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 1033.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
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]
]
},
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 475.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"2. Local Maxima": {
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"3. Local Minima": null
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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"2. Local Maxima": null,
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 364.",
"2. Local Maxima": null,
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} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 442.",
"2. Local Maxima": null,
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
294,
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]
]
}
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 503.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
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[
270,
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},
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": null,
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 884.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
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]
}
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 423.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
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},
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 469.",
"2. Local Maxima": null,
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} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"2. Local Maxima": {
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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] | {
"1. Frame Length": "The total frame length is: 586.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
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"3. Local Minima": null
} |
Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 399.",
"2. Local Maxima": null,
"3. Local Minima": null
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 338.",
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Grounding represents whether and to what extent both feet are grounded. Near the maximum value, both feet are in contact with the ground, and near the minimum value, both legs are far from the ground with a large extent equals to jump and small extent equals to walk. Specifically, a peak value of 0.7 corresponds to actions like jumping, 0.9 to actions like walking or running.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 525.",
"2. Local Maxima": null,
"3. Local Minima": null
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": {
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[
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[
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]
},
"3. Local Minima": null
} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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"2. Local Maxima": null,
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 396.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 400.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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"1. Frame Length": null,
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[
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]
},
"3. Local Minima": null
} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
162,
195
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]
}
} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 513.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 342.",
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
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"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
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[
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]
}
} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
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"1. Frame Length": "The total frame length is: 168.",
"2. Local Maxima": null,
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} |
Arm fold represents a quantification of the angle of the arm (wrist-elbow-shoulder angle). Near the maximum value, both arms are fully extended, and near the minimum value, both arms are folded.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
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] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
0,
2
],
[
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167
]
]
},
"3. Local Minima": null
} |