A robust appearance model for tracking human motions

We propose an original method for tracking people based on the construction of a 2-D human appearance model. The general framework, which is a region-based tracking approach, is applicable to any type of object. We show how to specialize the method for taking advantage of the structural properties of the human body. We segment its visible parts, construct and update the appearance model. This latter one provides a discriminative feature capturing both color and shape properties of the different limbs, making it possible to recognize people after they have temporarily disappeared. The method does not make use of skin color detection, which allows us to perform tracking under any viewpoint. The only assumption for the recognition is the approximate viewpoint correspondence during the matching process between the different models. Several results in complex situations prove the efficiency of the algorithm, which runs in near real time. Finally, the model provides an important clue for further human motion analysis process.

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