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Volumn , Issue PART 2, 2010, Pages 365-368

The facial expression recognition based on KPCA

Author keywords

[No Author keywords available]

Indexed keywords

DIMENSIONAL REDUCTION; FACIAL EXPRESSION RECOGNITION; FEATURE SETS; KERNEL PRINCIPAL COMPONENT ANALYSIS; NON-LINEAR METHODS; PRINCIPAL COMPONENTS;

EID: 78649249149     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICIP.2010.5565300     Document Type: Conference Paper
Times cited : (16)

References (13)
  • 1
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    • W. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld, "Face recognition: A literature survey," ACM Comput. Surv. J., ACM Press, New York, vol. 35, no. 4, pp.399-458, dec. 2003.
    • (2003) ACM Comput. Surv. J. , vol.35 , Issue.4 , pp. 399-458
    • Zhao, W.1    Chellappa, R.2    Phillips, P.J.3    Rosenfeld, A.4
  • 2
    • 0029304865 scopus 로고
    • Human and machine recognition of faces: A survey
    • May.
    • R. Chellappa, C. L. Wilson, and S. Sirohey, "Human and machine recognition of faces: A survey," Proc. IEEE, vol.83, no.5, pp. 705-741, May. 1995.
    • (1995) Proc. IEEE , vol.83 , Issue.5 , pp. 705-741
    • Chellappa, R.1    Wilson, C.L.2    Sirohey, S.3
  • 3
    • 0033734303 scopus 로고    scopus 로고
    • On internal representations in face recognition systems
    • Apr.
    • M.A. Grudin, "On Internal Representations in Face Recognition Systems," Pattern Recognition. J., vol.33, no.7, pp.1161-1177, Apr. 2000.
    • (2000) Pattern Recognition. J. , vol.33 , Issue.7 , pp. 1161-1177
    • Grudin, M.A.1
  • 5
    • 37749021581 scopus 로고    scopus 로고
    • Kernel principal component analysis and application in face recognition
    • Shanghai July.
    • G.H. Huang, and H.H. Shao, "Kernel Principal Component Analysis and Application in Face Recognition," Computer Engineering. J., Shanghai, vol.30, no.13, pp.13-14, July. 2004.
    • (2004) Computer Engineering. J. , vol.30 , Issue.13 , pp. 13-14
    • Huang, G.H.1    Shao, H.H.2
  • 9
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as akernel eigenvalue problem
    • B. Scholkopf, A. Smola, and K. Muller, "Nonlinear component analysis as akernel eigenvalue problem," Neural Computation, vol.10, pp.1299-1319, 1998.
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Scholkopf, B.1    Smola, A.2    Muller, K.3
  • 10
    • 14544297033 scopus 로고    scopus 로고
    • KCPA plus LDA: A complete kernel fisher discriminant framework for feature extraction and recognition
    • Feb.
    • J. Yang, A.F. Frangi, D. Zhang, and Z. Jin, "KCPA plus LDA: A complete kernel fisher discriminant framework for feature extraction and recognition," IEEE Trans, Pattern Anal. Mack Intell., vol.27, no.2, pp.230-244, Feb. 2005.
    • (2005) IEEE Trans, Pattern Anal. Mack Intell. , vol.27 , Issue.2 , pp. 230-244
    • Yang, J.1    Frangi, A.F.2    Zhang, D.3    Jin, Z.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.