In this paper we present an approach to track a moving body in a sequence of camera images by model adaptation. The parameters of a stick figure model are varied by using a stochastic search algorithm. The similarity of rendered model images and camera images of the user are used as quality measure. A refinement of the algorithm is introduced by using combined stereo views and relevance maps to infer responsible joint angles from the difference of successive input images. Finally, the successful application of various versions of the algorithm on sequences of synthetic images is demonstrated.
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