Mo2Cap2 Real-time Mobile 3D Motion Capture with a Cap-mounted Fisheye Camera

Mo2Cap2 : Real-time Mobile 3D Motion Capture with a Cap-mounted Fisheye Camera

We propose the first real-time system for the egocentric estimation of 3D human body pose in a wide range of unconstrained everyday activities. This setting has a unique set of challenges, such as mobility of the hardware setup, and robustness to long capture sessions with fast recovery from trackin...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 25(2019), 5 vom: 18. Mai, Seite 2093-2101
1. Verfasser: Xu, Weipeng (VerfasserIn)
Weitere Verfasser: Chatterjee, Avishek, Zollhofer, Michael, Rhodin, Helge, Fua, Pascal, Seidel, Hans-Peter, Theobalt, Christian
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:We propose the first real-time system for the egocentric estimation of 3D human body pose in a wide range of unconstrained everyday activities. This setting has a unique set of challenges, such as mobility of the hardware setup, and robustness to long capture sessions with fast recovery from tracking failures. We tackle these challenges based on a novel lightweight setup that converts a standard baseball cap to a device for high-quality pose estimation based on a single cap-mounted fisheye camera. From the captured egocentric live stream, our CNN based 3D pose estimation approach runs at 60 Hz on a consumer-level GPU. In addition to the lightweight hardware setup, our other main contributions are: 1) a large ground truth training corpus of top-down fisheye images and 2) a disentangled 3D pose estimation approach that takes the unique properties of the egocentric viewpoint into account. As shown by our evaluation, we achieve lower 3D joint error as well as better 2D overlay than the existing baselines
Beschreibung:Date Completed 10.02.2020
Date Revised 10.02.2020
published: Print-Electronic
Citation Status MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2019.2898650