A Note on Depth Estimation from Stereo Imaging Systems
: 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
Anahtar Kelimeler:
Stereovision, disparity, focal length, baseline
A Note on Depth Estimation from Stereo Imaging Systems
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.
Keywords:
Stereovision, disparity, focal length, baseline,
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- [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.
- ISSN: 2548-1304
- Yayın Aralığı: Yılda 2 Sayı
- Başlangıç: 2016
- Yayıncı: Ali KARCI
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