Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo hóa học: " Research Article Face Recognition Incorporating Ancillary Information"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Face Recognition Incorporating Ancillary Information | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 312849 11 pages doi 10.1155 2008 312849 Research Article Face Recognition Incorporating Ancillary Information Sang-Ki Kim Kar-Ann Toh and Sangyoun Lee School of Electrical and Electronic Engineering Yonsei University Seoul 120-749 South Korea Correspondence should be addressed to Sangyoun Lee syleee@yonsei.ac.kr Received 1 May 2007 Revised 26 July 2007 Accepted 16 September 2007 Recommended by Juwei Lu Due to vast variations of extrinsic and intrinsic imaging conditions face recognition remained to be a challenging computer vision problem even today. This is particularly true when the passive imaging approach is considered for robust applications. To advance existing recognition systems for face numerous techniques and methods have been proposed to overcome the almost inevitable performance degradation due to external factors such as pose expression occlusion and illumination. In particular the recent part-based method has provided noticeable room for verification performance improvement based on the localized features which have good tolerance to variation of external conditions. The part-based method however does not really stretch the performance without incorporation of global information from the holistic method. In view of the need to fuse the local information and the global information in an adaptive manner for reliable recognition in this paper we investigate whether such external factors can be explicitly estimated and be used to boost the verification performance during fusion of the holistic and part-based methods. Our empirical evaluations show noticeable performance improvement adopting the proposed method. Copyright 2008 Sang-Ki Kim et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1.