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Coloring Channel Representations for Visual Tracking
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6096-3648
2015 (English)In: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings / [ed] Rasmus R. Paulsen, Kim S. Pedersen, Springer, 2015, Vol. 9127, 117-129 p.Conference paper, Published paper (Refereed)
Abstract [en]

Visual object tracking is a classical, but still open research problem in computer vision, with many real world applications. The problem is challenging due to several factors, such as illumination variation, occlusions, camera motion and appearance changes. Such problems can be alleviated by constructing robust, discriminative and computationally efficient visual features. Recently, biologically-inspired channel representations \cite{felsberg06PAMI} have shown to provide promising results in many applications ranging from autonomous driving to visual tracking.

This paper investigates the problem of coloring channel representations for visual tracking. We evaluate two strategies, channel concatenation and channel product, to construct channel coded color representations. The proposed channel coded color representations are generic and can be used beyond tracking.

Experiments are performed on 41 challenging benchmark videos. Our experiments clearly suggest that a careful selection of color feature together with an optimal fusion strategy, significantly outperforms the standard luminance based channel representation. Finally, we show promising results compared to state-of-the-art tracking methods in the literature.

Place, publisher, year, edition, pages
Springer, 2015. Vol. 9127, 117-129 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 9127
Keyword [en]
Visual tracking, channel coding, color names
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-121003DOI: 10.1007/978-3-319-19665-7_10ISBN: 978-3-319-19664-0 (print)ISBN: 978-3-319-19665-7 (print)OAI: oai:DiVA.org:liu-121003DiVA: diva2:850742
Conference
Scandinavian Conference on Image Analysis
Available from: 2015-09-02 Created: 2015-09-02 Last updated: 2016-06-09Bibliographically approved

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Häger, GustavKhan, Fahad ShahbazFelsberg, Michael

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