Unsupervised learning using locally linear embedding: Experiments with face pose analysis

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 1, 2002, Pages 111-114

  Hadid, A ^a   Kouropteva, O ^a   Pietikainen M ^a  

^a UNIVERSITY OF OULU   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; CONVERGENCE OF NUMERICAL METHODS; EMBEDDED SYSTEMS; PARAMETER ESTIMATION; CLUSTERING ALGORITHMS; COMPUTATIONAL EFFICIENCY; FACE RECOGNITION; UNSUPERVISED LEARNING;

GLOBAL OPTIMALITY; LOCALLY LINEAR EMBEDDING (LLE); REAL-WORLD DATA;

LEARNING SYSTEMS; PATTERN RECOGNITION;

ASYMPTOTIC CONVERGENCE; COMPACT REPRESENTATION; DIMENSIONALITY REDUCTION; GLOBAL OPTIMALITY; HIGH DIMENSIONAL DATA; LOCALLY LINEAR EMBEDDING; NONLINEAR APPROACH; NONLINEAR MANIFOLDS;

EID: 8344253906     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (7)

1. R. O. Duda, P. E. Hart and D. G. Stork, "Pattern classification", Wiley, New York, NY 2000.
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5. S. Roweis and L. Saul, "Nonlinear dimensionality reduction by locally linear embedding", Science v. 290, No. 5500. Dec.22.2000, pp. 2323-2326.
6. J. B. Tenenbaum & al, "A global geometric framework for nonlinear dimensionality reduction", Science v. 290, No. 5500, Dec.22.2000, pp. 2319-2323.
7. J. Sherrah, S. Gong, and E.J. Ong, "Face distribution in similarity space under varying head pose", In Journal Image and Vision Computing, v. 19, No. 11, 2001, pp. 807-819.