Silhouette-based Gait Recognition Using Homography and PCA

호모그래피와 주성분 분석을 이용한 실루엣 기반 걸음걸이 인식

  • 정승도 (한양대학교 전자통신컴퓨터공학과) ;
  • 김수선 (한양여자대학 컴퓨터정보과) ;
  • 조태경 (상명대학교 정보통신공학과) ;
  • 최병욱 (한양대학교 정보통신대학) ;
  • 조정원 (제주대학교 컴퓨터교육과)
  • Published : 2006.01.01


In this paper, we propose a gait recognition method based on gait silhouette sequences. Features of gait are affected by the variation of gait direction. Therefore, we synthesize silhouettes to canonical form by using planar homography in order to reduce the effect of the variation of gait direction. The planar homography is estimated with only the information which exist within the gait sequences without complicate operations such as camera calibration. Even though gait silhouettes are generated from an individual person, fragments beyond common characteristics exist because of errors caused by inaccuracy of background subtraction algorithm. In this paper, we use the Principal Component Analysis to analyze the deviated characteristics of each individual person. PCA used in this paper, however, is not same as the traditional strategy used in pattern classification. We use PCA as a criterion to analyze the amount of deviation from common characteristic. Experimental results show that the proposed method is robust to the variation of gait direction and improves separability of test-data groups.


Gait Recognition;Planar Homography;Principal Component Analysis