Fast Hand-Gesture Recognition Algorithm For Embedded System

임베디드 시스템을 위한 고속의 손동작 인식 알고리즘

  • Hwang, Dong-Hyun (School of Computer Science and Engineering, Korea University of Technology and Education) ;
  • Jang, Kyung-Sik (School of Computer Science and Engineering, Korea University of Technology and Education)
  • Received : 2017.03.06
  • Accepted : 2017.03.30
  • Published : 2017.07.31


In this paper, we propose a fast hand-gesture recognition algorithm for embedded system. Existing hand-gesture recognition algorithm has a difficulty to use in a low performance system such as embedded systems and mobile devices because of high computational complexity of contour tracing method that extracts all points of hand contour. Instead of using algorithms based on contour tracing, the proposed algorithm uses concentric-circle tracing method to estimate the abstracted contour of fingers, then classify hand-gestures by extracting features. The proposed algorithm has an average recognition rate of 95% and an average execution time of 1.29ms, which shows a maximum performance improvement of 44% compared with algorithm using the existing contour tracing method. It is confirmed that the algorithm can be used in a low performance system such as embedded systems and mobile devices.

본 논문에서는 임베디드 시스템에 활용할 수 있는 고속의 손동작 인식 알고리즘을 제안한다. 기존의 손동작 인식 알고리즘은 손의 윤곽선을 구성하는 모든 점을 추출하는 윤곽선 추적 과정의 계산복잡도가 높기 때문에 임베디드 시스템, 모바일 디바이스와 같은 저성능의 시스템에서의 활용에 어려움이 있었다. 제안하는 알고리즘은 윤곽선 추적 알고리즘을 사용하는 대신 동심원 추적을 응용하여 추상화된 손가락의 윤곽선을 추정한 다음 특징을 추출하여 손동작을 분류한다. 제안된 알고리즘은 평균 인식률은 95%이고 평균 수행시간은 1.29ms로서 기존의 윤곽선 추적 방식을 사용하는 알고리즘에 비해 최대 44%의 성능향상을 보였고 임베디드 시스템, 모바일 디바이스와 같은 저성능의 시스템에서의 활용가능성을 확인하였다.



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