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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 Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 748483 18 pages doi 10.1155 2008 748483 Research Article Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image Zhanfeng Yue 1 Wenyi Zhao 2 and Rama Chellappa1 1 Center for Automation Research University of Maryland College Park MD 20742 USA 2 Vision Technologies Lab Sarnoff Corporation Princeton NJ 08873 USA Correspondence should be addressed to Zhanfeng Yue zyue@cfar.umd.edu Received 1 May 2007 Accepted 4 September 2007 Recommended by Juwei Lu Face recognition under varying pose is a challenging problem especially when illumination variations are also present. In this paper we propose to address one of the most challenging scenarios in face recognition. That is to identify a subject from a test image that is acquired under different pose and illumination condition from only one training sample also known as a gallery image of this subject in the database. For example the test image could be semifrontal and illuminated by multiple lighting sources while the corresponding training image is frontal under a single lighting source. Under the assumption of Lambertian reflectance the spherical harmonics representation has proved to be effective in modeling illumination variations for a fixed pose. In this paper we extend the spherical harmonics representation to encode pose information. More specifically we utilize the fact that 2D harmonic basis images at different poses are related by close-form linear transformations and give a more convenient transformation matrix to be directly used for basis images. An immediate application is that we can easily synthesize a different view of a subject under arbitrary lighting conditions by changing the coefficients of the spherical harmonics representation. A more important result is an efficient face recognition method based on the orthonormality of the linear transformations for solving the .
