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  - The model processes four distinct inputs, each corresponding to a specific set of features derived from video keypoints. Here’s how they are divided:
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  - Input 1, Input 2, Input 3:
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  - For each detected individual (up to 3 people), the model extracts 30 keypoints using MediaPipe.
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- - Each keypoint contains 3 features (x, y, z), resulting in 30 \times 3 = 90 features per frame.
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  - Input 4:
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  - Represents relative positional coordinates calculated from the 10 most important key joints (e.g., shoulders, elbows, knees) for all 3 individuals.
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  - These relative coordinates capture spatial relationships among individuals, crucial for contextual understanding.
 
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  - The model processes four distinct inputs, each corresponding to a specific set of features derived from video keypoints. Here’s how they are divided:
76
  - Input 1, Input 2, Input 3:
77
  - For each detected individual (up to 3 people), the model extracts 30 keypoints using MediaPipe.
78
+ - Each keypoint contains 3 features (x, y, z), resulting in 30 x 3 = 90 features per frame.
79
  - Input 4:
80
  - Represents relative positional coordinates calculated from the 10 most important key joints (e.g., shoulders, elbows, knees) for all 3 individuals.
81
  - These relative coordinates capture spatial relationships among individuals, crucial for contextual understanding.