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.