An efficient algorithm to compute eigenimages in PCA-based vision systems

Pattern Recognition

Volumn 32, Issue 5, 1999, Pages 851-864

  Zhao, Li ^a,b   Yang, Yee Hong ^a  

^a UNIVERSITY OF SASKATCHEWAN   (Canada)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Principal component analysis

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTATIONAL METHODS; COMPUTER VISION; EIGENVALUES AND EIGENFUNCTIONS; ERROR ANALYSIS; IMAGE SEGMENTATION; OBJECT RECOGNITION;

EIGENIMAGES; MULTISCALE METHODS; PRINCIPAL COMPONENT ANALYSIS; SCALE SPACE METHOD;

PATTERN RECOGNITION SYSTEMS;

ALGORITHM;

EID: 0033133852     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(98)00032-6     Document Type: Article

References (3)

1. [1] M.J. Black, A.D. Jepson, Eigen Tracking: robust matching and tracking of articulated object using view-based representation, ECCV'96, Cambridge, UK, 1996, pp. 329-342.
2. [2] K. Kukunaga, Introduction to Statistical Pattern Recognition, second edn., Academic Press, New York, 1990.
3. [3] T.D. Sanger, Optimal unsupervised learning in a single-layer linear feedforward neural network Neural Networks 2 (1989) 459-473.