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.
|Number of pages||12|
|Journal||IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics|
|Early online date||12 Apr 2010|
|Publication status||Published - Feb 2011|
Martínez Del Rincón, J., Makris, D., Orrite Uruñuela, C., & Nebel, J-C. (2011). Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 41(1), 26-37. . https://doi.org/10.1109/TSMCB.2010.2044041