A New Method for Detection and Initial Pose Estimation Based on Mumford-Shah Segmentation Functional

In this paper we describe a new method for detection and initial pose estimation of a person in a human computer interaction in an uncontrolled indoor environment. We used the Koepfler-Morel-Solimini mathematical formulation of Mumford-Shah segmentation functional adapted to color images. The idea is to obtain a system to detect the hands and face in a sequence of monocular or binocular images. The skin color is predefined and a procedure is parameterized to segment and recognize the homogeneous regions. Besides, we fit our results to a restriction that the two hands and face must be detected at the same time. We also use a biomechanical restriction to reach this initial estimation. So, the centroid of the blob is computed for every region. We explain the mathematical background segmentation, and region classification (hands, face, head and upper-torso). Finally, we present some interesting results and we implement the algorithm efficiently in order to obtain real time results processing standard video format.