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This paper discusses video motion capture, namely, 3D reconstruction of humanmotion from multi-camera images. After the Part Confidence Maps are computedfrom each camera image, the proposed spatiotemporal filter is applied todeliver the human motion data with accuracy and smoothness for human motionanalysis. The spatiotemporal filter uses the human skeleton and mixes temporalsmoothing in two-time inverse kinematics computations. The experimental resultsshow that the mean per joint position error was 26.1mm for regular motions and38.8mm for inverted motions.

Video Motion Capture from the Part Confidence Maps of Multi-Camera Images by Spatiotemporal Filtering Using the Human Skeletal Model