Online full body human motion tracking based on dense volumetric 3D reconstructions from multi camera setups

We present an approach for video based human motion capture using a static multi camera setup. The image data of calibrated video cameras is used to generate dense volumetric reconstructions of a person within the capture volume. The 3d reconstructions are then used to fit a 3d cone model into the data utilizing the Iterative Closest Point (ICP) algorithm. We can show that it is beneficial to use multi camera data instead of a single time of flight camera to gain more robust results in the overall tracking approach.