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Object Distance Estimation Based on Stereo Vision and Color Segmentation with Region Matching

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Advances in Visual Computing (ISVC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6455))

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Abstract

Human vision system relies on stereovision to determine object distance in the 3-D world. Human vision system achieves this by first locating the objects, then matching the corresponding objects seen by the left and right eyes, and finally using triangulation to estimate the object distance. Inspired by the same concept, this paper presents a depth estimation method based on stereo vision and color segmentation with region matching in CIE Lab color space. Firstly, an automatic seeded region growing approach for color segmentation in perceptually uniform color space was proposed. Then color region matching method was implemented after color segmentation. Thereafter, 3D reprojection method was employed to calculate depth distances. Experimental results are included to validate the proposed concept for object distance estimation.

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Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China

    Guangming Xiong, Xin Li, Junqiang Xi & Huiyan Chen

  2. Dept. of Electrical and Computer Engineering, Brigham Young University, Provo, Utah, USA

    Spencer G. Fowers

Authors
  1. Guangming Xiong
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  2. Xin Li
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  3. Junqiang Xi
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  4. Spencer G. Fowers
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  5. Huiyan Chen
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Ronald Chung

  6. Dyna Vox Systems, Pittsburgh, PA, USA

    Riad Hammound

  7. King Saud University, Riyadh, Saudi Arabia

    Muhammad Hussain

  8. Hewlett Packard Labs, Paolo Alto, CA, USA

    Tan Kar-Han

  9. The Ohio State University, Columbus, OH, USA

    Roger Crawfis

  10. Virtual Reality Lab, EPFL, Lausanne, Switzerland

    Daniel Thalmann

  11. NASA Ames Research Center, Clifton Park, NY, USA

    David Kao

  12. Kitware, Clifton Park, NY, USA

    Lisa Avila

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© 2010 Springer-Verlag Berlin Heidelberg

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Xiong, G., Li, X., Xi, J., Fowers, S.G., Chen, H. (2010). Object Distance Estimation Based on Stereo Vision and Color Segmentation with Region Matching. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17277-9_38

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  • DOI: https://doi.org/10.1007/978-3-642-17277-9_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17276-2

  • Online ISBN: 978-3-642-17277-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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