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Advanced Variable Window Stereo Matching Algorithm

  • Conference paper
Book cover Intelligence Science and Big Data Engineering (IScIDE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8261))

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Abstract

Variable window stereo matching methods overcome the disadvantages of fixed window methods. Using this base idea, an advanced Variable window stereo matching method is proposed. The method takes a certain threshold to determine matching windows. In order to improve the accuracy of matching further, a cost function using the non-parametric and gray value is proposed. The experimental results show that this method can generates more accurate disparity map.

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References

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Author information

Authors and Affiliations

  1. Hunan Institute of Science & Technology, Key Laboratory of Optimization and Control for Complex Systems, College of Hunan Province, Yueyang, 414006, China

    Guo Longyuan, Zhang Guoyun & Wu Jianhui

  2. School of Automation, Southeast University, Nanjing, 210096, China

    Guo Longyuan & Sun Changyin

Authors
  1. Guo Longyuan
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  2. Sun Changyin
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  3. Zhang Guoyun
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  4. Wu Jianhui
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Editor information

Editors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology, Xueyuan Road No. 30, 100083, Beijing, China

    Changyin Sun

  2. Department of Psychology, Peking University, Yiheyuan Road No. 5, 100871, Beijing, China

    Fang Fang

  3. Department of Computer Science and Technology, Nanjing University, Xianlin Avenue No. 163, 210023, Nanjing, China

    Zhi-Hua Zhou

  4. School of Automation, Southeast University, Sipailou No. 2, 210096, Nanjing, China

    Wankou Yang

  5. Institute of Automation, Chinese Academy of Sciences, No. 95 East Zhongguancun Road, 100190, Beijing, China

    Zhi-Yong Liu

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© 2013 Springer-Verlag Berlin Heidelberg

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Longyuan, G., Changyin, S., Guoyun, Z., Jianhui, W. (2013). Advanced Variable Window Stereo Matching Algorithm. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-42057-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42056-6

  • Online ISBN: 978-3-642-42057-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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