instruction
stringclasses 45
values | integer
sequencelengths 168
1.03k
| output
dict |
|---|---|---|
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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},
"3. Local Minima": null
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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35,
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43,
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[
288,
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[
290,
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[
294,
294
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},
"3. Local Minima": null
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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.",
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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: 168.",
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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.",
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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218,
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[
708,
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[
818,
841
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[
843,
845
],
[
922,
951
],
[
953,
957
],
[
960,
966
]
]
},
"3. Local Minima": null
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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": [
[
619,
620
],
[
623,
624
],
[
627,
632
]
]
}
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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.",
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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.",
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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.",
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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,
"3. Local Minima": null
} |
Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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[
295,
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[
325,
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[
369,
369
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"3. Local Minima": null
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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Kinetic energy represents the kinetic energy of the whole body. Near the maximum value, the movement is dynamic, indicating that the body is actively performing an action. Near the minimum value, the movement is static, suggesting that the body is preparing to act.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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"1. Frame Length": null,
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},
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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[
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}
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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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,
395
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]
},
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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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
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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[
0,
512
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]
},
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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"2. Local Maxima": null,
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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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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,
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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: 1033.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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,
1032
]
]
},
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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]
]
}
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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,
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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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]
}
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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": [
[
227,
267
]
]
},
"3. Local Minima": null
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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": [
[
176,
210
],
[
287,
325
]
]
}
} |
Potential energy represents the height level of the body's center of mass. Near the maximum value, it can be considered a jumping position, and near the minimum value, it can be considered a sitting position. Specifically, a value of 0.4 typically corresponds to the initial standing position. At a peak value of 1 corresponds to actions like significant jump, 0.7 to actions like small jump, 0 to actions like sitting.
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
} |