Human Body Part Segmentation of Interacting People by Learning Blob Models

In this paper, a scheme is proposed for solving segmentation problem when people engage in body contact in a video sequence. First, the body parts belonging to each interacting person are extracted using the deformable triangulation technique. The color blobs of each person are learned by Gaussian mixtures model on the fly before the person is interacting with another. Finally, those learned blob models are employed as decision criteria to segment each involved person out. The experimental results show that the proposed approach handles this kind of segmentation in an effective way.