Get Biometric Recognition: 6th Chinese Conference, CCBR 2011, PDF

By Zhaoxiang Zhang, Chao Wang, Yunhong Wang (auth.), Zhenan Sun, Jianhuang Lai, Xilin Chen, Tieniu Tan (eds.)

ISBN-10: 3642254489

ISBN-13: 9783642254482

ISBN-10: 3642254497

ISBN-13: 9783642254499

This publication constitutes the refereed lawsuits of the sixth chinese language convention on Biometric reputation, CCBR 2011, held in Beijing, China in December 2011. The 35 revised complete papers have been conscientiously reviewed and chosen from seventy one submissions. The papers are equipped in topical sections on difficulties in face; iris; hand biometrics; speaker; handwriting; gait; behavioral and tender biometrics; and security.

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Extra resources for Biometric Recognition: 6th Chinese Conference, CCBR 2011, Beijing, China, December 3-4, 2011. Proceedings

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3, (a) and (b) are two images from Yale Face Database B, The light direction of (a) is - 95, 0 , and (b) is( 95, 0) separately, (c) is right half of (a) with a mirror left-right transformation. (d) is left half of (b), (e) is a synthetic image whose left half is from (a) and right half from (b). (c) and (d) are almost the same except in the regions where specular reflection is happened. 3. 9223. This means that if the direction of the light turns to the symmetrical direction, the new image can be obtained just from the old one.

IEEE Transactions on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000) 13. : Kernel Eigenfaces vs Kernel Fisherfaces: Face recognition using kernel methods. In: Proceedings of International Conference on Automatic Face and Gesture Recognition, USA, Washington DC, pp. 215–220 (2002) 14. : AdaBoost Gabor Fisher Classifier for Face Recognition. , Tang, X. ) AMFG 2005. LNCS, vol. 3723, pp. 279–292. org Abstract. A good face recognition algorithm should be robust against variations caused by occlusion, expression or aging changes etc.

The sub server query in the database and return the query result to the main server. Finally the main server send the result message to the client. There are other two management program to supervise the database and all the clients. 2 29 Improved Algorithm of Face Recognition We applied the algorithm of 105 facial feature points to THFR, and developed a fusion algorithm to modify the final similarity. Our fusion algorithm goes as follows: 1. Suppose that the query image is I, and the client want to select top k entries with the similarity score > x.

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Biometric Recognition: 6th Chinese Conference, CCBR 2011, Beijing, China, December 3-4, 2011. Proceedings by Zhaoxiang Zhang, Chao Wang, Yunhong Wang (auth.), Zhenan Sun, Jianhuang Lai, Xilin Chen, Tieniu Tan (eds.)


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