Human body limbs tracking by multi-ocular vision

This article describes a tracking method of human body limbs from multi-ocular sequence of perspective images. These limbs and the associated articulations must be first modelled. During a learning step, we model the texture linked to the limbs. The lack of characteristic points on the skin is compensated by the wearing a non-repetitive texture tight. The principle of the method is based on the interpretation of image textured patterns as the SD perspective projections of points of the textured articulated model. An iterative Levenberg-Marquardt process is used to compute the model pose in accordance with the analysed image. The calculated attitude is filtered to predict the model pose in the following image of the sequence. The image patterns are extracted locally according to the textured articulated model in the predicted attitude. Tracking experiments, illustrated in this paper with cycling sequences, demonstrate the validity of the approach.