NDLI: Object-to-track association in a multisensor fusion system under the TBM framework

Content Provider	IEEE Xplore Digital Library
Author	Fayad, F. Hamadeh, K.
Copyright Year	2012
Description	Author affiliation: Department of Research and Development, Automation Systems and Diagnostics, Carry, NC, USA (Hamadeh, K.) \|\| Department of Computer & Communications Engineering, American University of Science and Technology, Beirut, Lebanon (Fayad, F.)
Abstract	Due to the increased interest in multiple-objects tracking, various methods have been recently proposed and applied in different applications such as: pedestrians identification and tracking, road vehicles detection and tracking, airplanes classification and tracking, etc. However, in presence of inter-object occlusion and sensor gaps, most of these methods result in tracking failure due to object-to-track association failure. This paper presents a new algorithm on object-to-track association in multi-sensor fusion systems under the transferable belief model framework. The proposed approach quantifies the belief on associating each detected object to each existing track, and takes into consideration the creation of new tracks by the non-associated objects.
Starting Page	1001
Ending Page	1006
File Size	178579
Page Count	6
File Format	PDF
ISBN	9781467303811
e-ISBN	9781467303828
e-ISBN	9781467303804
DOI	10.1109/ISSPA.2012.6310435
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-02
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heuristic algorithms Target tracking Numerical models Kalman filters Data models Probabilistic logic Complexity theory evidence theory object to track association multi-object tracking multisensor fusion transferable belief model
Content Type	Text
Resource Type	Article

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