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An Automatic Target Tracking System Based on Local and Global Features

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Genetic and Evolutionary Computing (ICGEC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 536))

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Abstract

Understanding human and object behaviors in video surveillance systems is an important factor and particular interest as far as public security is concerned. In this paper, we propose a novel method for object classification and tracking processes. It has been well recognized that the two processes play important roles in video surveillance system to make them intelligent. The proposed system is able to detect and classify human and non-human in different weather conditions. The system is capable of correctly tracking multiple objects despite occlusions and object interactions. Some experimental results are presented by using self-collected data.

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Acknowledgment

This work was supported by JSPS KAKENHI Grant Number JP15K14844.

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Authors and Affiliations

  1. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Thi Thi Zin & Kenshiro Yamada

Authors
  1. Thi Thi Zin
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  2. Kenshiro Yamada
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Corresponding author

Correspondence to Thi Thi Zin .

Editor information

Editors and Affiliations

  1. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, China

    Jerry Chun-Wei Lin

  3. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Chia-Hung Wang

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Xin Hua Jiang

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Zin, T.T., Yamada, K. (2017). An Automatic Target Tracking System Based on Local and Global Features. In: Pan, JS., Lin, JW., Wang, CH., Jiang, X. (eds) Genetic and Evolutionary Computing. ICGEC 2016. Advances in Intelligent Systems and Computing, vol 536. Springer, Cham. https://doi.org/10.1007/978-3-319-48490-7_30

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  • DOI: https://doi.org/10.1007/978-3-319-48490-7_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48489-1

  • Online ISBN: 978-3-319-48490-7

  • eBook Packages: EngineeringEngineering (R0)

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