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An Estimation Method of Skeleton Proportion for Hand’s Motion Capture

Volume 14, Number 1, January 2018, pp. 151-158
DOI: 10.23940/ijpe.18.01.p16.151158

Zhenning Zhang, Na Chen, Weiqing Li

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

(Submitted on October 25, 2017; Revised on November 30, 2017; Accepted on December 11, 2017)

Abstract:

Hand motion capture systems usually use the anatomical skeleton statistics size as the skeleton length of the virtual hand. The difference in user hands leads to error in the delicate hand tracking process. By analyzing the skeleton structure and movement characteristics of the hand, a three-dimensional hand skeleton model is constructed. Based on two specific gestures, the virtual hand model is calibrated. A skeleton proportion estimation algorithm based on specific attitudes is proposed. It can estimate the exact proportion of hand bone and realize the initial deviation correction of sensor data. In the meantime, the attitudes and positions of the virtual hand skeleton is calculated based on kinematics. Hand movement tracking is realized with accurate reduction. Using this method, a hand tracking and interaction system works fine.

 

References: 8

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