상세정보
학술대회
Face Recognition Based on Sparse Representation Classifier with Gabor-Edge Components Histogram
- 발행일
- 201211
- 출처
- International Conference on Signal Image Technology and Internet Based Systems (SITIS) 2012, pp.105-109
- 협약과제
- 12VG1100, 사람에 의한 안전위협의 실시간 인지를 위한 능동형 영상보안 서비스용 원거리 (CCTV 주간환경 5m이상) 사람 식별 및 검색 원천기술 개발, 유장희
- 초록
- We describe a new method for recognizing humans by their face, which is robust to the variations of facial imaging conditions, with high accuracy. The human face recognition system consists of three components: i) a new face descriptor based on edge component histogram and its variance between pixels; ii) Gabor-edge components histogram for facial image representation, combining the Gabor wavelet and the proposed edge components histogram; iii) a sparse representation classifier for the face recognition. The effective and robust face recognition with high accuracy is achieved by the Gabor-edge components histogram and the sparse representation classifier. In experiments, higher face recognition performances, which are 99.45% on ETRI database and 99.41% on XM2VTS database, have been achieved. © 2012 IEEE.
- KSP 제안 키워드
- Edge component, Face Recognition system, Face descriptor, Facial image representation, Gabor Wavelet, High accuracy, Human Face Recognition, Robust face recognition, Three components, new method, sparse representation classifier