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Proceedings of SAI Intelligent Systems Conference

IntelliSys 2020: Intelligent Systems and Applications pp 724–736Cite as

Discriminative Context-Aware Correlation Filter Network for Visual Tracking

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1250))

Abstract

In recent years, discriminative correlation filter (DCF) based trackers using convolutional features have received great attention due to their accuracy in online object tracking. However, the convolutional features of these DCF trackers are mostly extracted from convolutional networks trained for other vision tasks like object detection, which may limit the tracking performance. Moreover, under the challenge of fast motion and motion blur, the tracking performance usually decreases due to the lack of context information. In this paper, we present an end-to-end trainable discriminative context-aware correlation filter network, namely DCACFNet, which integrates context-aware correlation filter (CACF) into the fully-convolutional Siamese network. Firstly, the CACF is modeled as a differentiable layer in the DCACFNet architecture, which can back-propagate the localization error to the convolutional layers. Then, a novel channel attention module is embedded into the DCACFNet architecture to improve the target adaption of the whole network. Finally, this paper proposes a novel high-confidence update strategy to avoid the model corruption under the challenging of occlusion and out-of-view. Extensive experimental evaluations on two tracking benchmarks, OTB-2013 and OTB-2015, demonstrate that the proposed DCACFNet achieves the competitive tracking performance.

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Acknowledgments

This research is partially supported by National Natural Science Foundation of China (No.61876018, No.61976017).

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Authors and Affiliations

  1. Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China

    Xinjie Wang & Weibin Liu

  2. School of Software Engineering, Beijing Jiaotong University, Beijing, 100044, China

    Weiwei Xing

Authors
  1. Xinjie Wang
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  2. Weibin Liu
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  3. Weiwei Xing
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Corresponding author

Correspondence to Weibin Liu .

Editor information

Editors and Affiliations

  1. Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Wang, X., Liu, W., Xing, W. (2021). Discriminative Context-Aware Correlation Filter Network for Visual Tracking. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1250. Springer, Cham. https://doi.org/10.1007/978-3-030-55180-3_55

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