Leveraging long-term predictions and online learning in agent-based multiple person tracking
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 399-410 |
Journal / Publication | IEEE Transactions on Circuits and Systems for Video Technology |
Volume | 25 |
Issue number | 3 |
Online published | 29 Jul 2014 |
Publication status | Published - Mar 2015 |
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DOI | DOI |
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Attachment(s) | Documents
Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-84924354253&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(d14057c8-8bfe-40e2-83ce-a869befa67ff).html |
Abstract
We present a multiple-person tracking algorithm, based on combining particle filters (PFs) and reciprocal velocity obstacle (RVO), an agent-based crowd model that infers collision-free velocities so as to predict a pedestrian's motion. In addition to position and velocity, our tracking algorithm can estimate the internal goals (desired destination or desired velocity) of the tracked pedestrian in an online manner, thus removing the need to specify this information beforehand. Furthermore, we leverage the longer term predictions of RVO by deriving a higher order PF, which aggregates multiple predictions from different prior time steps. This yields a tracker that can recover from short-term occlusions and spurious noise in the appearance model. Experimental results show that our tracking algorithm is suitable for predicting pedestrians' behaviors online without needing scene priors or hand-annotated goal information, and improves tracking in real-world crowded scenes under low frame rates.
Research Area(s)
- pedestrian motion model, Pedestrian tracking, video surveillance, Particle filter (PF)
Citation Format(s)
Leveraging long-term predictions and online learning in agent-based multiple person tracking. / Liu, Wenxi; Chan, Antoni B.; Lau, Rynson W. H. et al.
In: IEEE Transactions on Circuits and Systems for Video Technology, Vol. 25, No. 3, 03.2015, p. 399-410.
In: IEEE Transactions on Circuits and Systems for Video Technology, Vol. 25, No. 3, 03.2015, p. 399-410.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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