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A Note on Depth Estimation from Stereo Imaging Systems

Year 2016, Volume: 1 Issue: 1, 8 - 13, 01.12.2016

Abstract

The depth extraction
from visual information is one of underpinning research area of robotics and
there is a growing trend in development of autonomous and intelligent systems for
real-life applications. These unmanned systems need reliable depth estimations in
order to move in three-dimensional space, autonomously. Inspiring from
biological vision systems, stereo imaging systems promise a solution for the depth
estimation from binocular image pairs provided by stereo cameras. One of the
major problems in the depth estimation from the stereo image pair is low depth
resolution. This paper discusses the depth resolution problem and presents a depth
resolution analysis for stereo imaging systems.

References

  • [1] Tomas Montserrat, Jaume Civit, Oscar Divorra Escoda, Jose-Luis Landabaso, Depth estimation based on multiview matching with depth/color segmentation and memory efficient belief propagation. In 2009 16th IEEE International Conference on Image Processing (ICIP),2009, pp. 2353-2356.
  • [2] Hoon Yoo, Joon-Jae Lee, and Byung-Gook Lee, "Depth extraction of three-dimensional objects using block matching for slice images in synthetic aperture integral imaging." Applied optics 50.29 (2011): 5624-5629.
  • [3] M. Bertozzi, A. Broggi, and A. Fascioli, “Vision-based intelligent vehicles: State of the art and perspectives,” Robotics and Autonomous Systems, vol. 32, pp. 1–16, 2000.
  • [4] Mohamed El Ansari, St´ephane Mousset, Abdelaziz Bensrhair, George Bebis, Temporal Consistent Fast Stereo Matching for Advanced Driver Assistance Systems (ADAS), 2010 IEEE Intelligent Vehicles Symposium University of California, San Diego, CA, 2010,pp.825-831
  • [5] Kuo-Hsien Hsia, Shao-Fan Lien and Juhng-Perng Su (2012). Stereo Matching Method and Height Estimation for Unmanned Helicopter, Machine Vision - Applications and Systems, Dr. Fabio Solari (Ed.), ISBN: 978-953-51-0373-8, InTech, Available from: http://www.intechopen.com/books/machine-vision-applications-andsystems/ stereo-matching-method-and-height-estimation-for-unmanned-helicopter
  • [6] D. Scharstein and R. Szeliski, “A taxonomy and evaluation of dense two-frame stereo sorrespondence algorithms,” International Journal of Computer Vision, vol. 47, no. 1-3, pp. 7–42, 2002.
  • [7] G.P. Otto and T.K. Chau. A region-growing algorithm for matching of terrain images. Image and Vision Computing, 7(2):83-94, 1989.
  • [8] Y. Boykov, O. Veksler and R. Zabih, Fast Approximate Energy Minimization via Graph Cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 11, 2001.
  • [9] V. Kolmogorov and R. Zabih, Computing Visual Correspondence with Occlusions using Graph Cuts, IEEE International Conference on Computer Vision, Vol. I:508-515 2001.
  • [10] J. Sun, N.-N. Zheng and H.-Y. Shum, StereoMatching Using Belief Propagation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 7, July 2003.
  • [11] J. Sun, Y. Li, S. B. Kang and H.-Y. Shum, Symmetric Stereo Matching for Occlusion Handling, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. II:399-406, 2005.
  • [12] T. Kanade and M. Okutomi, “AStereo Matching Algorithm with an Adaptive Window: Theory and Experiment,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 9, pp. 920-932, Sept.1994.

A Note on Depth Estimation from Stereo Imaging Systems

Year 2016, Volume: 1 Issue: 1, 8 - 13, 01.12.2016

Abstract

: The
depth extraction from visual information is one of underpinning research area
of robotics and there is a growing trend in development of autonomous and
intelligent systems for real-life applications. These unmanned systems need
reliable depth estimations in order to move in three-dimensional space, autonomously.
Inspiring from biological vision systems, stereo imaging systems promise a
solution for the depth estimation from binocular image pairs provided by stereo
cameras. One of the major problems in the depth estimation from the stereo
image pair is low depth resolution. This paper discusses the depth resolution
problem and presents a depth resolution analysis for stereo imaging systems

References

  • [1] Tomas Montserrat, Jaume Civit, Oscar Divorra Escoda, Jose-Luis Landabaso, Depth estimation based on multiview matching with depth/color segmentation and memory efficient belief propagation. In 2009 16th IEEE International Conference on Image Processing (ICIP),2009, pp. 2353-2356.
  • [2] Hoon Yoo, Joon-Jae Lee, and Byung-Gook Lee, "Depth extraction of three-dimensional objects using block matching for slice images in synthetic aperture integral imaging." Applied optics 50.29 (2011): 5624-5629.
  • [3] M. Bertozzi, A. Broggi, and A. Fascioli, “Vision-based intelligent vehicles: State of the art and perspectives,” Robotics and Autonomous Systems, vol. 32, pp. 1–16, 2000.
  • [4] Mohamed El Ansari, St´ephane Mousset, Abdelaziz Bensrhair, George Bebis, Temporal Consistent Fast Stereo Matching for Advanced Driver Assistance Systems (ADAS), 2010 IEEE Intelligent Vehicles Symposium University of California, San Diego, CA, 2010,pp.825-831
  • [5] Kuo-Hsien Hsia, Shao-Fan Lien and Juhng-Perng Su (2012). Stereo Matching Method and Height Estimation for Unmanned Helicopter, Machine Vision - Applications and Systems, Dr. Fabio Solari (Ed.), ISBN: 978-953-51-0373-8, InTech, Available from: http://www.intechopen.com/books/machine-vision-applications-andsystems/ stereo-matching-method-and-height-estimation-for-unmanned-helicopter
  • [6] D. Scharstein and R. Szeliski, “A taxonomy and evaluation of dense two-frame stereo sorrespondence algorithms,” International Journal of Computer Vision, vol. 47, no. 1-3, pp. 7–42, 2002.
  • [7] G.P. Otto and T.K. Chau. A region-growing algorithm for matching of terrain images. Image and Vision Computing, 7(2):83-94, 1989.
  • [8] Y. Boykov, O. Veksler and R. Zabih, Fast Approximate Energy Minimization via Graph Cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 11, 2001.
  • [9] V. Kolmogorov and R. Zabih, Computing Visual Correspondence with Occlusions using Graph Cuts, IEEE International Conference on Computer Vision, Vol. I:508-515 2001.
  • [10] J. Sun, N.-N. Zheng and H.-Y. Shum, StereoMatching Using Belief Propagation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 7, July 2003.
  • [11] J. Sun, Y. Li, S. B. Kang and H.-Y. Shum, Symmetric Stereo Matching for Occlusion Handling, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. II:399-406, 2005.
  • [12] T. Kanade and M. Okutomi, “AStereo Matching Algorithm with an Adaptive Window: Theory and Experiment,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 9, pp. 920-932, Sept.1994.
There are 12 citations in total.

Details

Subjects Computer Software
Journal Section PAPERS
Authors

Barış Baykant Alagöz This is me

Publication Date December 1, 2016
Submission Date November 3, 2016
Acceptance Date November 24, 2016
Published in Issue Year 2016 Volume: 1 Issue: 1

Cite

APA Alagöz, B. B. (2016). A Note on Depth Estimation from Stereo Imaging Systems. Computer Science, 1(1), 8-13.

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