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The Real-Time Depth Map Obtainment Based on Stereo Matching

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Book cover Intelligent Data Analysis and Applications (ECC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 535))

Abstract

The depth measurement according stereo vision is a very popular method of measuring the depth information. But the calculation in stereo matching is large, time-consuming and in large errors in matching, when used in real-time systems to obtain depth information are often ineffective. This paper improves one of the local matching algorithms, builds a complete real-time system for calculating depth image with different SAD (Sum of Absolute Differences) matching window in different texture regions. In this paper, we capture images from the Bumblebee2 stereoscopic camera which mounted on a small unmanned car, then use Matlab calibrating the camera and do the calculation to correct the raw images and do stereo matching in VS2010 to get the depth map. This method is simple, real-time performance and adaptability, and the quality of the depth map calculated from this method is somewhat improved.

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References

  1. Se, S., Jasiobedzki, P.: Stereo-vision based 3d modeling for unmanned ground vehicles. In: Proceedings of SPIE - The International Society for Optical Engineering, vol. 6561(1), 65610X-65610X-12 (2007)

    Google Scholar 

  2. Kim, G.B., Chung, S.C.: An accurate and robust stereo matching algorithm with variable windows for 3d measurements. J. Mechatron. 14(6), 715–735 (2004)

    Article  MathSciNet  Google Scholar 

  3. Yoon, K.J., Kweon, I.S.: Adaptive support-weight approach for correspondence search. J IEEE Trans. Pattern Analy. Mach. Intell. 28(4), 650–656 (2006)

    Article  Google Scholar 

  4. Zhang, K., Lu, J., Lafruit, G.: Cross-based local stereo matching using orthogonal integral images. J IEEE Trans. Circ. Syst. Video Technol. 19(7), 1073–1079 (2009)

    Article  Google Scholar 

  5. Liu, F.C., Xie, M.H., Wang, W.: Stereo calibration method of binocular vision. J. Comput. Eng. Des. 32(4), 1508–1512 (2011)

    Google Scholar 

  6. Wang, Z.Z., Zhao, L.Y., Liu, Z.Z.: Binocular stereo vision distance measurement system based on a combination of matlab and openCV. J. Tianjin Univ. Technol. 1, 13 (2013)

    Google Scholar 

  7. Lin, H.Y., Jian, S., Liu, Y.M., Rong, C.: Camera calibration technique based on rectification of image aberration. J. Jilin Univ. 37(2), 433–437 (2007)

    Google Scholar 

  8. Wang, H., Zhiwen, X.U., Xie, K., Jie, L.I., Song, C.: Binocular measuring system based on openCV. J. Jilin Univ. 2, 13 (2014)

    Google Scholar 

  9. Guo, L.Y., Sun, C.Y., Zhang, G.Y., Wu, J.H.: Variable window stereo matching based on phase congruency. Appl. Mech. Mater. 380–384, 3998–4001 (2013)

    Article  Google Scholar 

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Acknowledgments

This paper is supported by the Project for the National Key Technology R&D Program under Grant No.2011BAC12B03, the Key Project of Beijing Municipal Education Commission under Grant No.KZ201310005004, Basic Research Foundation of BJUT under Grant No.002000514314011 and Scientific Innovation Platform under Grant No.002000546615022.

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Authors and Affiliations

  1. Multimedia Information Processing Group, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China

    Fei Wang, Kebin Jia & Jinchao Feng

Authors
  1. Fei Wang
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  2. Kebin Jia
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  3. Jinchao Feng
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Corresponding author

Correspondence to Jinchao Feng .

Editor information

Editors and Affiliations

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

    Jeng-Shyang Pan

  2. Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava , Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

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

    Tien-Wen Sung

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

    Xiao Dong Wang

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Wang, F., Jia, K., Feng, J. (2017). The Real-Time Depth Map Obtainment Based on Stereo Matching. In: Pan, JS., Snášel, V., Sung, TW., Wang, X. (eds) Intelligent Data Analysis and Applications. ECC 2016. Advances in Intelligent Systems and Computing, vol 535. Springer, Cham. https://doi.org/10.1007/978-3-319-48499-0_17

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  • DOI: https://doi.org/10.1007/978-3-319-48499-0_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48498-3

  • Online ISBN: 978-3-319-48499-0

  • eBook Packages: EngineeringEngineering (R0)

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