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Improved Saliency-Enhanced Multi-cue Correlation-Filter-Based Visual Tracking

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Image and Video Technology (PSIVT 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11854))

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Abstract

A discrete correlation-filter-based multi-cue-analysis framework is constructed by fusing different feature types to form potential candidate trackers that track the target independently. The selection of corresponding cues and the exploitation of their individual or combined strengths is a less researched topic especially in the context of ensemble tracking. Every candidate tracker from the ensemble is chosen according to the degree of its robustness per frame. We argue that, if each of the candidate trackers is guided by higher-level semantic information (i.e. pixel-wise saliency maps in ensemble-based tracker), this will make tracking better to cope with appearance or view point changes. Recently, saliency prediction using deep architectures have made this process accurate and fast. The formation of multiple candidate trackers by saliency-guided features along with other different handcrafted and hierarchical feature types enhances the robustness score for that specific tracker. It improved multiple tracker-based DCF frameworks in efficiency and accuracy as reported in our experimental evaluation, compared to state-of-the-art ensemble trackers.

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand

    Syeda Fouzia & Reinhard Klette

  2. Crown Lift Trucks Ltd., Auckland, New Zealand

    Mark Bell

Authors
  1. Syeda Fouzia
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  2. Mark Bell
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  3. Reinhard Klette
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Corresponding author

Correspondence to Syeda Fouzia .

Editor information

Editors and Affiliations

  1. Chonnam National University, Gwangju, Korea (Republic of)

    Chilwoo Lee

  2. Dalian University of Technology, Dalian, China

    Zhixun Su

  3. National Institute of Informatics, Tokyo, Japan

    Akihiro Sugimoto

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Fouzia, S., Bell, M., Klette, R. (2019). Improved Saliency-Enhanced Multi-cue Correlation-Filter-Based Visual Tracking. In: Lee, C., Su, Z., Sugimoto, A. (eds) Image and Video Technology. PSIVT 2019. Lecture Notes in Computer Science(), vol 11854. Springer, Cham. https://doi.org/10.1007/978-3-030-34879-3_19

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  • DOI: https://doi.org/10.1007/978-3-030-34879-3_19

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  • Print ISBN: 978-3-030-34878-6

  • Online ISBN: 978-3-030-34879-3

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