The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Robust Object Tracking via Sparse Collaborative Appearance Model
Abstract
In this paper, we propose a robust object tracking algorithm based on a sparse collaborative model that exploits both holistic templates and local representations to account for drastic appearance changes. Within the proposed collaborative appearance model, we develop a sparse discriminative classifier (SDC) and sparse generative model (SGM) for object tracking. In the SDC module, we present a classifier that separates the foreground object from the background based on holistic templates. In the SGM module, we propose a histogram-based method that takes the spatial information of each local patch into consideration. The update scheme considers both the most recent observations and original templates, thereby enabling the proposed algorithm to deal with appearance changes effectively and alleviate the tracking drift problem. Numerous experiments on various challenging videos demonstrate that the proposed tracker performs favorably against several state-of-the-art algorithms.
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Cites
The pascal visual object classes (VOC) challenge
Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599
Comaniciu, D., Ramesh, V., & Meer, P. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1195991 · Cited by 4,560
Locality-constrained Linear Coding for image classification
Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., & Gong, Y. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5540018 · Cited by 3,100
Incremental Learning for Robust Visual Tracking
Ross, D. A., Lim, J., Lin, R.-S., & Yang, M.-H. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-007-0075-7 · Cited by 3,061
Self-citationRobust object tracking via sparsity-based collaborative model
Zhong, W., Lu, H., & Yang, M.-H. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247882 · Cited by 990
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Cited by
Wu, Y., Lim, J., & Yang, M.-H. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2388226 · Cited by 3,371
Self-citationVisual Tracking with Fully Convolutional Networks
Wang, L., Ouyang, W., Wang, X., & Lu, H. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.357 · Cited by 983
Self-citationLong-term correlation tracking
Ma, C., Yang, X., Zhang, C., & Yang, M.-H. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299177 · Cited by 959
Self-citationDeep visual tracking: Review and experimental comparison
Li, P., Wang, D., Wang, L., & Lu, H. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2017.11.007 · Cited by 517
Self-citationA review of video surveillance systems
Elharrouss, O., Almaadeed, N., & Al-Maadeed, S. (2021) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2021.103116 · Cited by 283
Metadata
- Authors
- Zhong, W., Lu, H., & Yang, M.-H.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2014-05
- Volume
- 23
- Issue
- 5
- Pages
- 2356-2368
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2094274531
- Cited by
- 307
- References
- 5
- FWCI
- 45.40
- Type
- journal article
- Language
- en
- Open access
- closed
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