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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2008.12
- 수록면
- 1,676 - 1,687 (12page)
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초록· 키워드
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In this paper, we proposed a new multi-view human recognition method based on face and gait features detection algorithm. For getting the position of moving object, we used the different of two consecutive frames. And then, base on the extracted object, the first important characteristic, walking direction, will be determined by using the contour of head and shoulder region. If this individual appears in camera with frontal direction, we will use the face features for recognition. The face detection technique is based on the combination of skin color and Haar~like feature whereas eigen-images and PCA are used in the recognition stage. In the other case, if the walking direction is frontal view, gait features will be used. To evaluate the effect of this proposed and compare with another method, we also present some simulation results which are performed in indoor and outdoor environment. Experimental result shows that the proposed algorithm has better recognition efficiency than the conventional single view recognition method.
목차
ABSTRACT
1. INTRODUCTION
2. OVERVIEW OF PROPOSED METHOD FOR MULTI-VIEW HUMAN RECOGNITION
3. WALKING DIRECTION DETERMINING
4. FACE FEATURES EXTRACTION FOR FRONTAL VIEW RECOGNITION
5. GAIT FEATURES DETECTION FOR FRONTAL SIDE VIEW RECOGNITION
6. EXPERIMENTAL RESULTS
7. CONCLUSION
ACKNOWLEDGMENT
REFERENCES
참고문헌 (16)
참고문헌 신청
http://www.facedetection.com
B. Moghaddam / 1997 / Probabilistic Visual Learning for Object Representation / IEEE Transaction on Pattern Analysis and Machine Intelligence 19:696~710
C. Liu / 1998 / Probabilistic Reasoning Models for Face Recognition / Proc. of Computer Vision and Pattern Recognition :827~832
M. Pontil / 1998 / Support Vector Machines for 3-D Object Recognition / IEEE Transaction. on Pattern Analysis and Machine Intelligence 20:637~646
G. Guo / 2000 / Face Recognition by Support Vector Machines / Proc. of the International Conferences on Automatic Face and Gesture Recognition :196~201
B. Moghaddam / 1997 / Probabilistic Visual Learning for Object Representation / IEEE Transaction on Pattern Analysis and Machine Intelligence 19:696~710
C. Liu / 1998 / Probabilistic Reasoning Models for Face Recognition / Proc. of Computer Vision and Pattern Recognition :827~832
M. Pontil / 1998 / Support Vector Machines for 3-D Object Recognition / IEEE Transaction. on Pattern Analysis and Machine Intelligence 20:637~646
G. Guo / 2000 / Face Recognition by Support Vector Machines / Proc. of the International Conferences on Automatic Face and Gesture Recognition :196~201
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UCI(KEPA) : I410-ECN-0101-2012-004-004431808