The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
A Linear Programming Approach for Multiple Object Tracking
Abstract
We propose a linear programming relaxation scheme for the class of multiple object tracking problems where the inter-object interaction metric is convex and the intra-object term quantifying object state continuity may use any metric. The proposed scheme models object tracking as a multi-path searching problem. It explicitly models track interaction, such as object spatial layout consistency or mutual occlusion, and optimizes multiple object tracks simultaneously. The proposed scheme does not rely on track initialization and complex heuristics. It has much less average complexity than previous efficient exhaustive search methods such as extended dynamic programming and is found to be able to find the global optimum with high probability. We have successfully applied the proposed method to multiple object tracking in video streams.
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Citations
Cites
A Boosted Particle Filter: Multitarget Detection and Tracking
Okuma, K., Taleghani, A., de Freitas, N., Little, J. J., & Lowe, D. G. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24670-1_3 · Cited by 1,019
Self-citationAn MCMC-Based Particle Filter for Tracking Multiple Interacting Targets
Khan, Z., Balch, T., & Dellaert, F. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24673-2_23 · Cited by 367
Application of 0-1 integer programming to multitarget tracking problems
Morefield, C. (1977) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1977.1101500 · Cited by 281
Poore, A. B. (1994) · Computational Optimization and Applications · doi:10.1007/bf01299390 · Cited by 243
Robust People Tracking with Global Trajectory Optimization
Berclaz, J., Fleuret, F., & Fua, P. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06) · doi:10.1109/cvpr.2006.258 · Cited by 201
Visual Hand Tracking Using Nonparametric Belief Propagation
Sudderth, E. B., Mandel, M. I., Freeman, W. T., & Willsky, A. S. (2005) · 2004 Conference on Computer Vision and Pattern Recognition Workshop · doi:10.1109/cvpr.2004.474 · Cited by 167
Multi-Target Tracking - Linking Identities using Bayesian Network Inference
Nillius, P., Sullivan, J., & Carlsson, S. (2006) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2006.198 · Cited by 142
Finding the best set of K paths through a trellis with application to multitarget tracking
Wolf, J. K., Viterbi, A. M., & Dixon, G. S. (1989) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/7.18692 · Cited by 97
An LP-based algorithm for the data association problem in multitarget tracking
Storms, P. P. A., & Spieksma, F. C. R. (2003) · Computers & Operations Research · doi:10.1016/s0305-0548(02)00057-6 · Cited by 69
Cited by
Towards Real-Time Multi-Object Tracking
Wang, Z., Zheng, L., Liu, Y., Li, Y., & Wang, S. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58621-8_7 · Cited by 1,195
Multiple Object Tracking Using K-Shortest Paths Optimization
Berclaz, J., Fleuret, F., Turetken, E., & Fua, P. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.21 · Cited by 1,015
TrackFormer: Multi-Object Tracking with Transformers
Meinhardt, T., Kirillov, A., Leal-Taixe, L., & Feichtenhofer, C. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.00864 · Cited by 1,081
“Graphs have been used for track association and longterm re-identification by formulating the problem as a maximum flow (minimum cost) optimization [3] with distance based [20, 36, 62] or learned costs [24].”
MethodTracking Without Bells and Whistles
Bergmann, P., Meinhardt, T., & Leal-Taixe, L. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00103 · Cited by 1,110
Globally-optimal greedy algorithms for tracking a variable number of objects
Pirsiavash, H., Ramanan, D., & Fowlkes, C. C. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995604 · Cited by 790
Metadata
- Authors
- Jiang, H., Fels, S., & Little, J. J.
- Venue
- 2007 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2007-06
- Pages
- 1-8
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2124541566
- Cited by
- 316
- References
- 9
- FWCI
- 6.57
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Jiang, H., Fels, S., & Little, J. J. (2007). A Linear Programming Approach for Multiple Object Tracking. 2007 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2007.383180
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