Single view motion tracking by depth and silhouette information

Abstract

In this work1 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. © Springer-Verlag Berlin Heidelberg 2007.