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

인접 프레임의 시간적 상관 관계를 이용한 회전에 강인한 손 모양 인식

  • Received : 2010.02.23
  • Accepted : 2010.10.06
  • Published : 2010.11.30


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.


Grant : u-로봇 HRI 솔루션 및 핵심 소자 기술 개발

Supported by : 한국전자통신 연구원


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