2019/12/09 by Takuya Ohashi, Ohashi, Takuya, Yosuke Ikegami +7
Computer Science · Engineering · #Advanced Vision and Imaging #Human Motion and Animation #Human Pose and Action Recognition #cs.CV #cs.RO
paper · pdf · doi:10.48550/arxiv.1912.03880
International Conference on Intelligent Robots and Systems (IROS), 2018
arxiv created 2019/12/10 · arxiv updated 2019/12/11
This paper discusses video motion capture, namely, 3D reconstruction of human motion from multi-camera images. After the Part Confidence Maps are computed from each camera image, the proposed spatiotemporal filter is applied to deliver the human motion data with accuracy and smoothness for human motion analysis. The spatiotemporal filter uses the human skeleton and mixes temporal smoothing in two-time inverse kinematics computations. The experimental results show that the mean per joint position error was 26.1mm for regular motions and 38.8mm for inverted motions.