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3D human pose tracking based on depth camera and dynamic programming optimization

Depth camera has gained much more attention in applications of human computer interactivity. In this paper, we present an approach to tracking 3D human pose by constructing/estimating an articulated upper body joint model from depth data captured by Kinect camera. The system first calibrates the human pose parameters by processing the depth data of an initial pose. After that, the dynamic programming (DP) approach is performed for the tracking of joints, intending to optimize their observations in depth images and conformation to some physical constraints. Experiments show satisfactory tracking results. A performance comparison with the PrimeSense NITE program is also given. The current implementation presents a processing speed of over 30 frames per second.