Abstract. In this work 3 a combination of depth and silhouette information is presented to track the motion of a human from a single view. Depth data is acquired from a Photonic Mixer Device (PMD), which measures the time-of-flight of light. Correspondences between the silhouette of the projected model and the real image are established in a novel way, that can handle cluttered non-static backgrounds. Pose is estimated by Nonlinear Least Squares, which handles the underlying dynamics of the kinematic chain directly. Analytic Jacobians allow pose estimation with 5 FPS.

Motion capture has important applications in different areas such as biomechanics, computer animation, and human-computer interaction. Current motion capture methods use passive markers that are attached to different body parts of the subject and are therefore intrusive in nature. In applications such as pathological human movement analysis, these markers may introduce an unknown artifact in the motion, and are, in general, cumbersome. We present computer vision based methods for performing markerless human motion capture. We model the human body as a set of super-quadrics connected in an articulated structure and propose algorithms to estimate the parameters of the model from video sequences. We compute a volume data (voxel) representation from the images and combine bottom-up approach with top down approach guided by our knowledge of the model. We propose a tracking algorithm that uses this model to track human pose. The tracker uses an iterative framework akin to an Iterated Extended Kalman Filter to estimate articulated human motion using multiple cues that combine both spatial and temporal information in a novel manner. We provide preliminary results using data collected from 8-16 cameras. The emphasis of our work is on models and algorithms that are able to scale with respect to the requirement for accuracy. Our ultimate objective is to build an end-to-end system that can integrate the above mentioned components into a completely automated markerless motion capture system. 1