Quasi Monte Carlo partitioned filtering for Visual Human Motion Capture

Visual Human Motion Capture (HMC) is a motivating challenge in the Computer Vision community as it enables lots of applications. Many methods have been proposed among which Particle Filters (PF) meet a great success. In this paper, we propose a new algorithm, mixing advantages of the PARTITIONED scheme and quasi random methods. We use a trinocular visual system to propose a comparative study of this particle filter against four other classical ones with respect to a ground truth provided by a commercial HMC system.