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Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics

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4 Author(s)
Jesús Martinez del Rincon ; Digital Imaging Research Centre, Kingston University , U.K. ; Dimitrios Makris ; Carlos Orrite Urunuela ; Jean-Christophe Nebel

In this paper, a novel framework for visual tracking of human body parts is introduced. The approach presented demonstrates the feasibility of recovering human poses with data from a single uncalibrated camera by using a limb-tracking system based on a 2-D articulated model and a double-tracking strategy. Its key contribution is that the 2-D model is only constrained by biomechanical knowledge about human bipedal motion, instead of relying on constraints that are linked to a specific activity or camera view. These characteristics make our approach suitable for real visual surveillance applications. Experiments on a set of indoor and outdoor sequences demonstrate the effectiveness of our method on tracking human lower body parts. Moreover, a detail comparison with current tracking methods is presented.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)  (Volume:41 ,  Issue: 1 )