Best-Buddies Similarity for robust template matching

Tali Dekel; Shaul Oron; Michael Rubinstein; Shai Avidan; William T. Freeman

doi:10.1109/CVPR.2015.7298813

Best-Buddies Similarity for robust template matching

Tali Dekel, Shaul Oron, Michael Rubinstein, Shai Avidan, William T. Freeman

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

156 Scopus citations

Abstract

We propose a novel method for template matching in unconstrained environments. Its essence is the Best-Buddies Similarity (BBS), a useful, robust, and parameter-free similarity measure between two sets of points. BBS is based on counting the number of Best-Buddies Pairs (BBPs) - pairs of points in source and target sets, where each point is the nearest neighbor of the other. BBS has several key features that make it robust against complex geometric deformations and high levels of outliers, such as those arising from background clutter and occlusions. We study these properties, provide a statistical analysis that justifies them, and demonstrate the consistent success of BBS on a challenging real-world dataset.

Original language	English
Title of host publication	IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Publisher	IEEE Computer Society
Pages	2021-2029
Number of pages	9
ISBN (Electronic)	9781467369640
DOIs	https://doi.org/10.1109/CVPR.2015.7298813
State	Published - 14 Oct 2015
Event	IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 - Boston, United States Duration: 7 Jun 2015 → 12 Jun 2015

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume	07-12-June-2015
ISSN (Print)	1063-6919

Conference

Conference	IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Country/Territory	United States
City	Boston
Period	7/06/15 → 12/06/15

Access to Document

10.1109/CVPR.2015.7298813

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Dekel, T., Oron, S., Rubinstein, M., Avidan, S., & Freeman, W. T. (2015). Best-Buddies Similarity for robust template matching. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 (pp. 2021-2029). Article 7298813 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 07-12-June-2015). IEEE Computer Society. https://doi.org/10.1109/CVPR.2015.7298813

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title = "Best-Buddies Similarity for robust template matching",

abstract = "We propose a novel method for template matching in unconstrained environments. Its essence is the Best-Buddies Similarity (BBS), a useful, robust, and parameter-free similarity measure between two sets of points. BBS is based on counting the number of Best-Buddies Pairs (BBPs) - pairs of points in source and target sets, where each point is the nearest neighbor of the other. BBS has several key features that make it robust against complex geometric deformations and high levels of outliers, such as those arising from background clutter and occlusions. We study these properties, provide a statistical analysis that justifies them, and demonstrate the consistent success of BBS on a challenging real-world dataset.",

author = "Tali Dekel and Shaul Oron and Michael Rubinstein and Shai Avidan and Freeman, {William T.}",

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doi = "10.1109/CVPR.2015.7298813",

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Dekel, T, Oron, S, Rubinstein, M, Avidan, S & Freeman, WT 2015, Best-Buddies Similarity for robust template matching. in IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015., 7298813, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 07-12-June-2015, IEEE Computer Society, pp. 2021-2029, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, United States, 7/06/15. https://doi.org/10.1109/CVPR.2015.7298813

Best-Buddies Similarity for robust template matching. / Dekel, Tali; Oron, Shaul; Rubinstein, Michael et al.
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015. IEEE Computer Society, 2015. p. 2021-2029 7298813 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 07-12-June-2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Best-Buddies Similarity for robust template matching

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