This curve is descriptive of the kind of motion exhibited by the head of the individual. By training our system to recognize motions based on curves like this, the objective is to recognize different motions for different parts of the body, and by combining different motions, infer different human activities in a video. Motion of the tip of the nose of the person in the video clip. The horizontal motion. Once faces in the first frame are detected, a chroma chart is computed for each detected individual and that chroma chart is used to detect and track faces in subsequent frames.
Chroma chart representing the skin color of one individual.
Brightness of points show the likelihoods of different chromas belonging to the skin. Segmented images to extracted skin regions. The templates used to extract the exact color templates in the video that are used to detect corresponding faces in the subsequent frame in the video. Patterns from the first fame, 10th frame, 30th frame in the video that are used to detect and verify the faces in the subsequent frame in the video. The following video clip shows the tracking result of regions from two individuals.