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Hand posture recognition robust to rotation using temporal correlation between adjacent frames  

Lee, Seong-Il (KAIST 전기 및 전자공학과)
Min, Hyun-Seok (KAIST 정보통신공학과)
Shin, Ho-Chul (한국전자통신연구원)
Lim, Eul-Gyoon (한국전자통신연구원)
Hwang, Dae-Hwan (한국전자통신연구원)
Ro, Yong-Man (KAIST 전기 및 전자공학과)
Publication Information
Journal of Korea Multimedia Society / v.13, no.11, 2010 , pp. 1630-1642 More about this Journal
Abstract
Recently, there is an increasing need for developing the technique of Hand Gesture Recognition (HGR), for vision based interface. Since hand gesture is defined as consecutive change of hand posture, developing the algorithm of Hand Posture Recognition (HPR) is required. Among the factors that decrease the performance of HPR, we focus on rotation factor. To achieve rotation invariant HPR, we propose a method that uses the property of video that adjacent frames in video have high correlation, considering the environment of HGR. The proposed method introduces template update of object tracking using the above mentioned property, which is different from previous works based on still images. To compare our proposed method with previous methods such as template matching, PCA and LBP, we performed experiments with video that has hand rotation. The accuracy rate of the proposed method is 22.7%, 14.5%, 10.7% and 4.3% higher than ordinary template matching, template matching using KL-Transform, PCA and LBP, respectively.
Keywords
Hand posture recognition; Template update; Human-computer interaction;
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