Human Gesture Detection Based on 3D Blobs and Skeleton Model

This paper presents a gesture tracking method using 3D blobs and a skeleton model for interactive application. A disparity map is obtained from stereo matching based on GPGPU and we generate 3D foreground blobs using depth information. The distribution of 3D blobs is applied to determine the human position combined with the face and torso detection. The skeleton model for an upper body is fitted successively to a median axis in the area with more 3D blobs from the shoulder parts to the hands. We examine the position and color of the 3D blobs for robust tracking of the gesture parts. The reconstructed trajectory is classified into one of the gesture set.