DocumentCode
1451568
Title
Deformable template recognition of multiple occluded objects
Author
Mardia, Kanti V. ; Qian, Wei ; Shah, Druti ; De Souza, Kevin M A
Author_Institution
Dept. of Stat., Leeds Univ., UK
Volume
19
Issue
9
fYear
1997
fDate
9/1/1997 12:00:00 AM
Firstpage
1035
Lastpage
1042
Abstract
Based on deformable templates, the paper formulates an integrated and flexible Bayesian recognition system of multiple occluded objects. Various local dependence properties of the model are obtained to reduce the computational cost with the increase in the number of objects. Numerical results for a synthetic image and for a real image of mushrooms are discussed
Keywords
Bayes methods; computational complexity; image recognition; object recognition; computational cost; deformable template recognition; integrated flexible Bayesian recognition system; local dependence properties; multiple occluded objects; mushrooms; numerical results; Bayesian methods; Computational efficiency; Computational geometry; Deformable models; Iterative methods; Knowledge based systems; Markov random fields; Object recognition; Robots; Stochastic processes;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.615452
Filename
615452
Link To Document