NDLI: Multi-target tracking by enhancing the kernelised correlation filter-based tracker

Content Provider	IET Digital Library
Author	Kwon, J. Kim, K. S. Cho, K.
Abstract	A new tracking method based on the kernelised correlation filter (KCF) method is proposed. The tracker improves KCF-based trackers by adding seven proposed components, namely, the motion model, background subtraction, occlusion handling, hijacking handling, object proposal, bounding box modification, and object re-detection. With these components, the tracker robustly tracks multiple targets despite severe occlusion, rapid motion, and the presence of other objects with similar appearance. The visual tracking performance is evaluated by using challenging basketball game videos. Experiments demonstrate that the tracker outperforms the original KCF tracker and other state-of-the-art tracking methods.
Starting Page	1358
Ending Page	1360
Page Count	3
ISSN	00135194
Volume Number	53
e-ISSN	1350911X
Issue Number	Issue 20, Sep (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/53/20
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2017.2129
Journal	Electronics Letters
Publisher Date	2017-09-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Background Subtraction Basketball Game Videos Bounding Box Modification Computer Vision And Image Processing Technique Correlation Method Filtering Method in Signal Processing Filtering Theory Hijacking Handling Humanities Computing Image Motion Analysis KCF-based Trackers Kernelised Correlation Filter-based Tracker Motion Model Multitarget Tracking Object Detection Object Proposal Object Redetection Object Tracking Occlusion Handling Optical, Image And Video Signal Processing Sport Target Tracking Video Signal Processing Visual Tracking Performance Evaluation
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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