JOURNAL ARTICLE

Object matching using deformable templates

Anil K. JainYu ZhongSridhar Lakshmanan

Year: 1996 Journal:   IEEE Transactions on Pattern Analysis and Machine Intelligence Vol: 18 (3)Pages: 267-278   Publisher: IEEE Computer Society

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 matching Template Artificial intelligence Computer science Computer vision Pattern recognition (psychology) Invariant (physics) Cognitive neuroscience of visual object recognition Matching (statistics) Object (grammar) Active shape model Rotation (mathematics) Probabilistic logic Object detection Image (mathematics) Mathematics Segmentation

Metrics

518
Cited By
68.93
FWCI (Field Weighted Citation Impact)
37
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing and 3D Reconstruction
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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