Visual multiple-object tracking for unknown clutter rate

Kim, D 2018, 'Visual multiple-object tracking for unknown clutter rate', IET Computer Vision, vol. 12, no. 5, pp. 728-734.

Document type: Journal Article
Collection: Journal Articles

Title Visual multiple-object tracking for unknown clutter rate
Author(s) Kim, D
Year 2018
Journal name IET Computer Vision
Volume number 12
Issue number 5
Start page 728
End page 734
Total pages 7
Publisher The Institution of Engineering and Technology
Abstract In multi-object tracking applications, model parameter tuning is a prerequisite for reliable performance. In particular, it is difficult to know statistics of false measurements due to various sensing conditions and changes in the field of views. In this study, the authors are interested in designing a multi-object tracking algorithm that handles unknown false measurement rate. The recently proposed robust multi-Bernoulli filter is employed for clutter estimation while generalised labelled multi-Bernoulli filter is considered for target tracking. Performance evaluation with real videos demonstrates the effectiveness of the tracking algorithm for real-world scenarios.
Subject Computer Vision
DOI - identifier 10.1049/iet-cvi.2017.0600
Copyright notice © The Institution of Engineering and Technology 2018.
ISSN 1751-9632
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
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