Improved context-aware correlation filter tracking

Nanyang Wang; Zhihong Xie; Nan Huang

doi:10.1117/12.2514676

29 October 2018 Improved context-aware correlation filter tracking

Nanyang Wang, Zhihong Xie, Nan Huang

Proceedings Volume 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence; 108360S (2018) https://doi.org/10.1117/12.2514676
Event: 2018 International Conference on Image, Video Processing and Artificial Intelligence, 2018, Shanghai, China

Abstract

For the problem that the correlation filter (CF) trackers can not effectively deal with the occlusion and cause the loss of the target, a large number of tracking algorithm improvements focus on the combination of more powerful features to enrich the apparent model of the target. However, this only helps to discriminate the target from background within a small neighborhood. In this paper, an improved context-aware correlation filtering framework is introduced, which can comprehensively integrate global context information in the correlation filter tracker to effectively deal with the target's fast motion, occlusion and other issues. And the criterion APCE is used to judge the reliability of the tracking result, thus adjusting the threshold adaptively for model updating. A large number of experiments demonstrate that this framework has a significant impact on the performance of many CF trackers with only a modest impact on frame rate.

Citation Download Citation

Nanyang Wang, Zhihong Xie, and Nan Huang "Improved context-aware correlation filter tracking", Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 108360S (29 October 2018); https://doi.org/10.1117/12.2514676

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