User-Adaptable Hand Pose Estimation Technique for Human-Robot Interaction
Albert Causo*, Etsuko Ueda**, Kentaro Takemura*,
Yoshio Matsumoto***, Jun Takamatsu*, and Tsukasa Ogasawara*
*Nara Institute of Science and Technology (NAIST), 8916-5 Takayama-cho, Ikoma City, Nara 630-0192, Japan
**Nara Sangyo University 3-12-1 Tatsunokita, Sango-cho, Ikoma-gun, Nara 636-8503, Japan
***Intelligent Systems Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
Hand pose estimation using a multi-camera system allows natural non-contact interfacing unlike when using bulky data gloves. To enable any user to use the system regardless of gender or physical differences such as hand size, we propose hand model individualization using only multiple cameras. From the calibration motion, our method estimates the finger link lengths as well as the hand shape by minimizing the gap between the hand model and observation. We confirmed the feasibility of our proposal by comparing 1) actual and estimated link lengths and 2) hand pose estimation results using our calibrated hand model, a prior hand model and data obtained from data glove measurements.
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