Object recognition by flexible template matching using genetic algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 588 LNCS, Issue , 1992, Pages 852-856

  Hill, A ^a   Taylor, C J ^a   Cootes, T ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; GENETIC ALGORITHMS; OBJECT RECOGNITION;

TEMPLATE MODELS; ULTRASOUND IMAGES;

TEMPLATE MATCHING;

EID: 84962822183     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-55426-2_98     Document Type: Conference Paper

References (6)

1. Cootes T. F., Cooper D. H., Taylor C. J., Graham J.: A Trainable Method of Parametric Shape Description. Proa British Machine Vision Conference, Glasgow (1991) Springer Verlag 54-61.
2. Goldberg D. E.: Genetic Algorithms in Search, Optimisation and Machine Learning. Addison-Wesley (1989).
3. Holland J. H.: Adaptation in Natural and Artificial Systems. University of Michegan Press, Ann Arbor (1975).
4. Lipson P., Yuille A.L, O’Keeffe D., Cavanaugh J., Taaffe J., Rosenthal D.: Deformable Templates for Feature Extraction from Medical Images. Proc. 1st European Conference on Computer Vision, Lecture Notes in Computer Science, Springer-Verlag, (1990) 413-417.
5. Pentland A., Sclaroff S.: Closed-Form Solutions for Physically Based Modeling and Recognition. IEEE Trans, on Pattern Analysis and Machine Intelligence 13(7) (1991) 715-729.
6. Yuille A.L, Cohen D.S., Hallinan P.: Feature Extraction from Faces using Deformable Templates. Proc Computer Vision, San Diego (1989) 104-109.