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A Method for the 3D Reconstruction Based on Edge Detection and Feature Extraction

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Transactions on Edutainment XI

Part of the book series: Lecture Notes in Computer Science ((TEDUTAIN,volume 8971))

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Abstract

This paper presents a method for three-dimensional reconstruction from images that can be used to identify obstacles based on a single omnidirectional image obtained by an omnidirectional stereo vision optical device (OSVOD). The OSVOD is a novel catadioptric system based on a common perspective camera coupled with two hyperbolic mirrors. The images captured by OSVOD are unwrapped into cylinder panoramic images, which are then examined for stereo matching along vertical epiploar lines. Given two images of a space point obtained by this vision system, the 3D coordinates of the point can be calculated by using triangulation. An algorithm of the quick stereo matching method based on Canny edge and SIFT feature points is proposed and the result of 3D reconstruction and depth map are obtained. From the results, we can find that the 3D reconstruction accuracy can be accepted for mobile robots’ obstacle detection and navigation tasks.

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (No. 60905046).

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Authors and Affiliations

  1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, People’s Republic of China

    Liangcheng Su & Fei Jia

Authors
  1. Liangcheng Su
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  2. Fei Jia
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Corresponding author

Correspondence to Liangcheng Su .

Editor information

Editors and Affiliations

  1. Hangzhou Normal University, Hangzhou, China

    Zhigeng Pan

  2. Professor of Pervasive Computing, City University London, London, United Kingdom

    Adrian David Cheok

  3. University of Education Weingarten, Weingarten, Germany

    Wolfgang Mueller

  4. Zejiang University, Hangzhou, China

    Mingmin Zhang

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Su, L., Jia, F. (2015). A Method for the 3D Reconstruction Based on Edge Detection and Feature Extraction. In: Pan, Z., Cheok, A., Mueller, W., Zhang, M. (eds) Transactions on Edutainment XI. Lecture Notes in Computer Science(), vol 8971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48247-6_3

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  • DOI: https://doi.org/10.1007/978-3-662-48247-6_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48246-9

  • Online ISBN: 978-3-662-48247-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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