4 June 2019 Real-time robust complementary visual tracking with redetection scheme
Haijun Wang, Shengyan Zhang, Hongjuan Ge
Author Affiliations +
Abstract
Recently, correlation filter-based trackers have been widely investigated due to their high efficiency and robustness. However, most of them use a fixed cosine window to deal with boundary effects and ignore the reliability of tracking results, which results in poor tracking performance when the target endures severe occlusion and large appearance variation. In order to deal with these issues, we propose a tracking framework with an adaptive cosine window, which is composed of a reliability estimation module and a redetection module. First, we incorporate the object likelihood map into the traditional fixed cosine window to form an adaptive cosine window, which can enlarge the searching region and effectively cope with boundary effects. Second, the peak-to-sidelobe ratio of HOG-based correlation response map and the color score of each frame are adopted to estimate the reliability of tracking results. Third, we introduce the Siamese tracker to redetect targets in case of tracking failures. Finally, a target pyramid scheme is built to deal with scale variation. Extensive experiments on the OTB-2013, OTB-2015, TemplateColor, UAV123@10 fps, and VOT-2015 demonstrate that our proposed method outperforms favorably against the state-of-the-art methods with real-time tracking speed.
© 2019 SPIE and IS&T 1017-9909/2019/$25.00 © 2019 SPIE and IS&T
Haijun Wang, Shengyan Zhang, and Hongjuan Ge "Real-time robust complementary visual tracking with redetection scheme," Journal of Electronic Imaging 28(3), 033020 (4 June 2019). https://doi.org/10.1117/1.JEI.28.3.033020
Received: 19 March 2019; Accepted: 9 May 2019; Published: 4 June 2019
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KEYWORDS
Optical tracking

Germanium

Feature extraction

Image filtering

Reliability

Electronic filtering

Performance modeling

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