• May 15, 2019 News!Vol.7, No.5- Vol.8, No.4 has been indexed by EI (Inspec).   [Click]
  • Aug 01, 2018 News! [CFP] 2020 the annual meeting of IJMO Editorial Board, ECDMO 2020, will be held in Athens, Greece, February 15-17, 2020.   [Click]
  • Sep 30, 2019 News!Vol 9, No 6 has been published with online version. 12 original aritcles from 6 countries are published in this issue.    [Click]
General Information
    • ISSN: 2010-3697  (Online)
    • Abbreviated Title: Int. J. Model. Optim.
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET), EBSCO, etc.
    • E-mail ijmo@iacsitp.com
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2019 Vol.9(2): 72-76 ISSN: 2010-3697
DOI: 10.7763/IJMO.2019.V9.687

Online Appearance-Motion Coupling for Multi-Person Tracking in Videos

Bonan Cuan, Khalid Idrissi, and Christophe Garcia
Abstract—Multi-person tracking in videos is a promising but challenging visual task. Recent progress in this field has introduced deep convolutional features as appearance models, which achieve robust tracking results when coupled with proper motion models. However, model failures that often cause severe tracking problems have not been well discussed and addressed in previous work. In this paper, we propose a solution using online detection of such failures and accordingly adjusting the coupling between appearance and motion models. The strategy is to let the functional models take over when certain models face data association ambiguity and simultaneously suppress the influence of inappropriate observations during the model update. Experimental results have proven the benefit of our proposed improvement.

Index Terms—Multiple object tracking, deep neural network, online learning, tracking-by-detection, multiple hypothesis tracking.

The authors are with the Université de Lyon, CNRS, INSA-Lyon, LIRIS, UMR5205, F-69621 France (e-mails: bonan.cuan@insa-lyon.fr, khalid.idrissi@insa-lyon.fr, christophe.garcia@insa-lyon.fr).

[PDF]

Cite: Bonan Cuan, Khalid Idrissi, and Christophe Garcia, "Online Appearance-Motion Coupling for Multi-Person Tracking in Videos," International Journal of Modeling and Optimization vol. 9, no. 2, pp. 72-76, 2019.

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