Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition Jian Yang, David Zhang zhniu@jdl.ac.cn

Jian YangEDUCATIONS Ph.D Department of Computer Science, Nanjing University of Science and Technology (NUST), 2002M.S Applied Mathematics from Changsha Railway University, 1998B.Sc Mathematics from the Xuzhou Normal University, 1995

PUBLICATIONSJian Yang; Frangi, A.F.; Jing-Yu Yang; David Zhang; Zhong Jin; KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume 27, Issue 2, Feb. 2005 Page(s):230 - 244 Jian Yang, David Zhang, Alejandro F. Frangi, Jing-Yu Yang: Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 26(1): 131-137 (2004) Jian Yang, Hui Ye, David Zhang: A new LDA-KL combined method for feature extraction and its generalisation. Pattern Anal. Appl. 7(1): 40-50 (2004) Jian Yang, Zhong Jin, Jingyu Yang, David Zhang, Alejandro F. Frangi: Essence of kernel Fisher discriminant: KPCA plus LDA. Pattern Recognition 37(10): 2097-2100 (2004) Jian Yang, Jing-Yu Yang, Alejandro F. Frangi, David Zhang: Uncorrelated Projection Discriminant Analysis And Its Application To Face Image Feature Extraction. IJPRAI 17(8): 1325-1347 (2003) Jian Yang, Jing-Yu Yang, Alejandro F. Frangi: Combined Fisherfaces framework. Image Vision Comput. 21(12): 1037-1044 (2003) Jian Yang, Jing-Yu Yang: Why can LDA be performed in PCA transformed space? Pattern Recognition 36(2): 563-566 (2003) Jian Yang, Jing-Yu Yang, David Zhang, Jian-feng Lu: Feature fusion: parallel strategy vs. serial strategy. Pattern Recognition 36(6): 1369-1381 (2003) Jian Yang, Jing-Yu Yang: Generalized K-L transform based combined feature extraction. Pattern Recognition 35(1): 295-297 (2002) Jian Yang, Jing-Yu Yang, David Zhang: What's wrong with Fisher criterion? Pattern Recognition 35(11): 2665-2668 (2002) Jian Yang, Jing-Yu Yang: From image vector to matrix: a straightforward image projection technique - IMPCA vs. PCA. Pattern Recognition 35(9): 1997-1999 (2002)

David ZhangEDUCATIONS Ph.D Electrical & Computer Engineering, University of Waterloo, 1994 Ph.D Computer Science, Harbin Institute of Technology (HIT), 1985 M.S Computer Science, Harbin Institute of Technology (HIT), 1983 B.Sc Computer Science, Peking University, Beijing, 1974 EMPLOYMENT Adjunct Professor (2002- ) Department of System Design, University of Waterloo, Canada Guest/Adjunct Professor (2000- ) Shanghai Jiao Tong University / Tsinghua UniversityFull Professor (1999- ) Department of Computing, Hong Kong Polytechnic University (PolyU) Associate Professor (1995-1999) Department of Computer Science, City University of Hong Kong (CityU) Department of Computing, Hong Kong Polytechnic University (PolyU) Adjunct Professor / Department of Computer Science and Engineering Supervisor of PhD (1995- )Harbin Institute of Technology (HIT), China Associate Professor (1988-1991) National Key Lab of Pattern Recognition, Institute of Automation Chinese Academy of Science, Beijing, China Postdoctoral Fellow (1986-1988) Department of Automation, Tsinghua University, Beijing, China Lecturer (1974-1980) Department of Computer Science, Heilongjiang University, China

SELECTED HONORS Academic AwardsProject AwardsSupervised Student AwardsPatents SELECTED ACTIVITIES (1998 - ) Current Editorial Activities Conference Organization Industry Consultants Leaderships RESEARCH GRANTS (as Principal Investigator)(1996-) INVITED TALKSPARTIAL PUBLICATIONSBOOKSBOOK CHAPTERSSELECTED JOURNAL PAPERSSELECTED CONFERENCE PAPERS

:IEEE TPAMI:JANUARY 2004J. Yang, J.Y. Yang, From Image Vector to Matrix: A Straightforward Image Projection TechniqueIMPCA vs. PCA, Pattern Recognition, vol. 35, no. 9, pp. 1997-1999, 2002.

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INTRODUCTIONTWO-DIMENSIONAL PRINCIPAL COMPONENT ANALYSISIdea and AlgorithmFeature Extraction2DPCA-Based Image ReconstructionEXPERIMENTS AND ANALYSISExperiment on the ORL DatabaseExperiment on the AR DatabaseExperiment on the Yale DatabaseEvaluation of the Experimental ResultsCONCLUSION AND FUTURE WORK

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