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

Template matchingTemplateArtificial intelligenceComputer scienceComputer visionPattern recognition (psychology)Invariant (physics)Cognitive neuroscience of visual object recognitionMatching (statistics)Object (grammar)Active shape modelRotation (mathematics)Probabilistic logicObject detectionImage (mathematics)MathematicsSegmentation

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Publication Info

Year
1996
Type
article
Volume
18
Issue
3
Pages
267-278
Citations
518
Access
Closed

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Cite This

Anil K. Jain, Yu Zhong, Sridhar Lakshmanan (1996). Object matching using deformable templates. IEEE Transactions on Pattern Analysis and Machine Intelligence , 18 (3) , 267-278. https://doi.org/10.1109/34.485555

Identifiers

DOI
10.1109/34.485555