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Spatio-Temporal Context Tracking Algorithm Based on Master-Slave Memory Space Model

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Image and Graphics Technologies and Applications (IGTA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 875))

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Abstract

The spatio-temporal context (STC) tracking algorithm has the advantages of high tracking accuracy and speed, but it may update the target template incorrectly under complex background and interference conditions. A spatio-temporal context tracking algorithm based on master-slave memory space model is proposed in this paper. The algorithm introduces the memory mechanism of Human Visual System (HVS) into the template updating process of STC algorithm, and forms a memory-based update strategy by constructing the master and slave memory spaces. Meanwhile, a method for determining the target location from multi peak points of saliency is proposed. Experimental results indicate that the proposed algorithm has comparatively high accuracy and robustness in the case of the target under occlusion, attitude changes, the target missing and appearing, and illumination changes, etc.

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Acknowledgement

This work is supported by National Nature Science Foundation of China (NSFC) (81671787); Defense Industrial Technology Development Program (JCKY2016208B001)

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Authors and Affiliations

  1. School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China

    Xu Li, Yong Song, Yufei Zhao, Yun Li, Shangnan Zhao & Xin Yang

  2. Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing, 100081, China

    Xu Li, Yong Song, Yufei Zhao, Yun Li, Shangnan Zhao & Xin Yang

  3. Institute of Aviation Medicine, AF CPLA, Beijing, 100142, China

    Guowei Shi

Authors
  1. Xu Li
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  2. Yong Song
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  3. Yufei Zhao
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  4. Yun Li
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  5. Shangnan Zhao
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  6. Guowei Shi
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  7. Xin Yang
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Corresponding author

Correspondence to Yong Song .

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Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Yongtian Wang

  2. Beihang University, Beijing, China

    Zhiguo Jiang

  3. Peking University, Beijing, China

    Yuxin Peng

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© 2018 Springer Nature Singapore Pte Ltd.

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Li, X. et al. (2018). Spatio-Temporal Context Tracking Algorithm Based on Master-Slave Memory Space Model. In: Wang, Y., Jiang, Z., Peng, Y. (eds) Image and Graphics Technologies and Applications. IGTA 2018. Communications in Computer and Information Science, vol 875. Springer, Singapore. https://doi.org/10.1007/978-981-13-1702-6_21

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  • DOI: https://doi.org/10.1007/978-981-13-1702-6_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1701-9

  • Online ISBN: 978-981-13-1702-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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