Visual tracking using pertinent patch selection and masking

Dae Youn Lee; Jae Young Sim; Chang-Su Kim

doi:10.1109/CVPR.2014.446

Visual tracking using pertinent patch selection and masking

Dae Youn Lee, Jae Young Sim, Chang-Su Kim

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

39 Citations (Scopus)

Abstract

A novel visual tracking algorithm using patch-based appearance models is proposed in this paper. We first divide the bounding box of a target object into multiple patches and then select only pertinent patches, which occur repeatedly near the center of the bounding box, to construct the foreground appearance model. We also divide the input image into non-overlapping blocks, construct a background model at each block location, and integrate these background models for tracking. Using the appearance models, we obtain an accurate foreground probability map. Finally, we estimate the optimal object position by maximizing the likelihood, which is obtained by convolving the foreground probability map with the pertinence mask. Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art tracking algorithms significantly in terms of center position errors and success rates.

Original language	English
Title of host publication	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Publisher	IEEE Computer Society
Pages	3486-3493
Number of pages	8
ISBN (Electronic)	9781479951178, 9781479951178
DOIs	https://doi.org/10.1109/CVPR.2014.446
Publication status	Published - 2014 Sept 24
Event	27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014 - Columbus, United States Duration: 2014 Jun 23 → 2014 Jun 28

Publication series

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

Other

Other	27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014
Country/Territory	United States
City	Columbus
Period	14/6/23 → 14/6/28

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition

Access to Document

10.1109/CVPR.2014.446

Cite this

Lee, D. Y., Sim, J. Y., & Kim, C.-S. (2014). Visual tracking using pertinent patch selection and masking. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 3486-3493). Article 6909841 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). IEEE Computer Society. https://doi.org/10.1109/CVPR.2014.446

Visual tracking using pertinent patch selection and masking. / Lee, Dae Youn; Sim, Jae Young; Kim, Chang-Su.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 2014. p. 3486-3493 6909841 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

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

Lee, DY, Sim, JY & Kim, C-S 2014, Visual tracking using pertinent patch selection and masking. in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition., 6909841, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, pp. 3486-3493, 27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, United States, 14/6/23. https://doi.org/10.1109/CVPR.2014.446

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Visual tracking using pertinent patch selection and masking

Abstract

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