Enhancing Linear Programming with Motion Modeling for Multi-target Tracking

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Abstract

In this paper we extend the minimum-cost network flow approach to multi-target tracking, by incorporating a motion model, allowing the tracker to better cope with longterm occlusions and missed detections. In our new method, the tracking problem is solved iteratively: Firstly, an initial tracking solution is found without the help of motion information. Given this initial set of tracklets, the motion at each detection is estimated, and used to refine the tracking solution.
Finally, special edges are added to the tracking graph, allowing a further revised tracking solution to be found, where distant tracklets may be linked based on motion similarity. Our system has been tested on the PETS S2.L1 and Oxford town-center sequences, outperforming the baseline system, and achieving results comparable with the current state of the art.
Original languageEnglish
Title of host publication2015 IEEE Winter Conference on Applications of Computer Vision (WACV)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages71-77
Number of pages7
ISBN (Print)978-1-4799-6682-0
DOIs
Publication statusPublished - 06 Jan 2015
EventWACV 2015: IEEE Winter Conference on Applications of Computer Vision - Hawaii, Waikoloa Beach, United States
Duration: 06 Jan 201509 Jan 2015

Conference

ConferenceWACV 2015: IEEE Winter Conference on Applications of Computer Vision
CountryUnited States
CityWaikoloa Beach
Period06/01/201509/01/2015

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  • Cite this

    McLaughlin, N., Martinez Del Rincon, J., & Miller, P. (2015). Enhancing Linear Programming with Motion Modeling for Multi-target Tracking. In 2015 IEEE Winter Conference on Applications of Computer Vision (WACV) (pp. 71-77). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WACV.2015.17