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Content Provider | IEEE Xplore Digital Library |
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Author | Duc Thanh Nguyen |
Copyright Year | 2014 |
Description | Author affiliation: Fac. of Inf. Technol., Nong Lam Univ., Ho Chi Minh City, Vietnam (Duc Thanh Nguyen) |
Abstract | This paper proposes a novel mean field-based Chamfer template matching method. In our method, each template is represented as a field model and matching a template with an input image is formulated as estimation of a maximum of posteriori in the field model. Variational approach is then adopted to approximate the estimation. The proposed method was applied for two different variants of Chamfer template matching and evaluated through the task of object detection. Experimental results on benchmark datasets including ETHZShapeClass and INRIAHorse have shown that the proposed method could significantly improve the accuracy of template matching while not sacrificing much of the efficiency. Comparisons with other recent template matching algorithms have also shown the robustness of the proposed method. |
Starting Page | 2425 |
Ending Page | 2432 |
File Size | 8357401 |
Page Count | 8 |
File Format | |
ISBN | 9781479951185 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.2014.311 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-06-23 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image edge detection Shape Estimation Computational modeling Vectors Accuracy Object detection object detection Chamfer template matching variational mean field |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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