DocumentCode :
759821
Title :
Object matching using deformable templates
Author :
Jain, Anil K. ; Zhong, Yu ; Lakshmanan, Sridhar
Author_Institution :
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
Volume :
18
Issue :
3
fYear :
1996
fDate :
3/1/1996 12:00:00 AM
Firstpage :
267
Lastpage :
278
Abstract :
We propose a general object localization and retrieval scheme based on object shape using deformable templates. Prior knowledge of an object shape is described by a prototype template which consists of the representative contour/edges, and a set of probabilistic deformation transformations on the template. A Bayesian scheme, which is based on this prior knowledge and the edge information in the input image, is employed to find a match between the deformed template and objects in the image. Computational efficiency is achieved via a coarse-to-fine implementation of the matching algorithm. Our method has been applied to retrieve objects with a variety of shapes from images with complex background. The proposed scheme is invariant to location, rotation, and moderate scale changes of the template
Keywords :
Bayes methods; image matching; image segmentation; object recognition; probability; visual databases; Bayesian scheme; deformable templates; edge information; image database; image segmentation; object localization; object matching; object shape; optimisation; probabilistic deformation; Bayesian methods; Computational efficiency; Computer science; Image databases; Image retrieval; Image segmentation; Information retrieval; Object recognition; Prototypes; Shape;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.485555
Filename :
485555
Link To Document :
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