Development of wrist contour measuring device for an interface using hand shape recognition

Recently, gesture recognition is widely used as interface. Popular gestures are mainly arm motion and whole body motion. Although hand shape is a good sign that can express rich information with small motions, few applications are in practical use. That is because the existing methods have several problems: blocks of finger sense and interference with finger motion, restrictions of hand position and posture, and complex initial configurations. In this study, we try to recognize hand shapes by observing the wrist contour, which varies with finger motions. We have developed a robust wrist-watch-type device that captures wrist contour, and have collected data from a substantial number of subjects. With the collected data, we conduct hand shape recognition experiments in several conditions. To overcome the positioning deviations and individual differences, two feature types are designed. Through the experiment, potential of the features is confirmed, and some effective features are picked up. In addition, concerning the design of recognition target properties, we examine the number of target hand shapes and the combination of hand shapes through the experiment, and several clues for target design are revealed.

[1]  Hans Hagen,et al.  Flexible Gesture Recognition for Immersive Virtual Environments , 2006, Tenth International Conference on Information Visualisation (IV'06).

[2]  Mircea Nicolescu,et al.  A Review on Vision-Based Full DOF Hand Motion Estimation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[3]  Masamichi Shimosaka,et al.  Hand shape classification with a wrist contour sensor: development of a prototype device , 2011, UbiComp '11.

[4]  M. Yoshikawa,et al.  Real-Time Hand Motion Estimation Using EMG Signals with Support Vector Machines , 2006, 2006 SICE-ICASE International Joint Conference.

[5]  Sanjeev Sofat,et al.  Vision Based Hand Gesture Recognition , 2009 .

[6]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.

[7]  K. Nagata,et al.  A Classification Method of Hand Movements Using Multi Channel Electrode , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[8]  Vladimir Pavlovic,et al.  Hand Gesture Modeling, Analysis, and Synthesis , 1995 .

[9]  Kiyoshi Hoshino,et al.  Copycat hand — robot hand imitating human motions at high speed and with high accuracy , 2007, Adv. Robotics.