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arXiv 1701.00142cs.CV

EgoCap: Egocentric Marker-less Motion Capture with Two Fisheye Cameras (Extended Abstract)

Max Planck Institute for Informatics(马克斯·普朗克信息学研究所);Intel Visual Computing Institute(英特尔视觉计算研究院);University of Bath(巴斯大学)

Helge Rhodin, Christian Richardt, Dan Casas, Eldar Insafutdinov, Mohammad Shafiei, Hans-Peter Seidel, Bernt Schiele, Christian Theobalt

英文摘要:

Marker-based and marker-less optical skeletal motion-capture methods use an outside-in arrangement of cameras placed around a scene, with viewpoints converging on the center. They often create discomfort by possibly needed marker suits, and their recording volume is severely restricted and often constrained to indoor scenes with controlled backgrounds. We therefore propose a new method for real-time, marker-less and egocentric motion capture which estimates the full-body skeleton pose from a lightweight stereo pair of fisheye cameras that are attached to a helmet or virtual-reality headset. It combines the strength of a new generative pose estimation framework for fisheye views with a ConvNet-based body-part detector trained on a new automatically annotated and augmented dataset. Our inside-in method captures full-body motion in general indoor and outdoor scenes, and also crowded scenes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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