iccv iccv2013 iccv2013-28 iccv2013-28-reference knowledge-graph by maker-knowledge-mining
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Author: Jinwei Ye, Yu Ji, Jingyi Yu
Abstract: Traditional stereo matching assumes perspective viewing cameras under a translational motion: the second camera is translated away from the first one to create parallax. In this paper, we investigate a different, rotational stereo model on a special multi-perspective camera, the XSlit camera [9, 24]. We show that rotational XSlit (R-XSlit) stereo can be effectively created by fixing the sensor and slit locations but switching the two slits’ directions. We first derive the epipolar geometry of R-XSlit in the 4D light field ray space. Our derivation leads to a simple but effective scheme for locating corresponding epipolar “curves ”. To conduct stereo matching, we further derive a new disparity term in our model and develop a patch-based graph-cut solution. To validate our theory, we assemble an XSlit lens by using a pair of cylindrical lenses coupled with slit-shaped apertures. The XSlit lens can be mounted on commodity cameras where the slit directions are adjustable to form desirable R-XSlit pairs. We show through experiments that R-XSlitprovides apotentially advantageous imaging system for conducting fixed-location, dynamic baseline stereo.
[1] Y. Boykov and V. Kolmogorov. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE transactions on Pattern Analysis and Machine Intelligence, 26(9): 1124–1 137, September 2004.
[2] Y. Boykov, O. Veksler, and R. Zabih. Efficient approximate energy minimization via graph cuts. IEEE transactions on Pattern Analysis and Machine Intelligence, 20(12): 1222– 1239, November 2001 .
[3] Y. Ding and J. Yu. Multiperspective distortion correction using collineations. InAsian Conference on Computer Vision (ACCV), 2007.
[4] D. Feldman, T. Pajdla, and D. Weinshall. On the epipolar geometry of the crossed-slits projection. In IEEE International Conference on Computer Vision (ICCV), 2003.
[5] D. Gallup, J.-M. Frahm, P. Mordohai, and M. Pollefeys. Variable baseline/resolution stereo. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
[6] R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, NY, USA, 2 edition, 2003.
[7] V. Kolmogorov and R. Zabih. What energy functions can be minimized via graph cuts? IEEE transactions on Pattern Analysis andMachine Intelligence, 26(2): 147–159, February 2004.
[8] M. Levoy and P. Hanrahan. Light field rendering. In ACM SIGGRAPH, pages 31–42, 1996.
[9] T. Pajdla. Geometry of two-slit camera. Technical Report CTU-CMP-2002-02, Czech Technical University.
[10] T. Pajdla. Epipolar geometry of some non-classical cameras. In Proc. of Computer Vision Winter Workshop, Slovenian Pattern Recognition Society, pages 223–233, 2001.
[11] T. Pajdla. Stereo with oblique cameras. In IEEE Workshop on Stereo and Multi-Baseline Vision, pages 85–91, 2001 .
[12] T. Pajdla. Stereo with oblique cameras. International Journal on Computer Vision, 47(1-3): 161–170, April 2002.
[13] M. Pollefeys, R. Koch, and L. J. V. Gool. A simple and efficient rectification method for general motion. In IEEE International Conference on Computer Vision (ICCV), 1999.
[14] J. Ponce. What is a camera? In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
[15] D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal on Computer Vision, 47(1-3):7–42, April 2002.
[16] S. M. Seitz. The space of all stereo images. In IEEE International Conference on Computer Vision (ICCV), 2001 .
[17] S. M. Seitz and J. Kim. The space of all stereo images. International Journal on Computer Vision, 48(1):21–38, June 2002.
[18] S. M. Seitz and J. Kim. Multiperspective imaging. IEEE Computer Graphics and Applications, 23(6): 16–19, Novem-
[19]
[20]
[21]
[22]
[23]
[24] 496 ber 2003. T. Storms. The Crossed-slit Anamorphoser: An Analysis of Its Characteristics and Utility in Cartography. University of Washington, 198 1. R. Szeliski and D. Scharstein. Sampling the disparity space image. IEEE transactions on Pattern Analysis and Machine Intelligence, 26(3):419–425, March 2004. J. Ye, Y. Ji, and J. Yu. Manhattan scene understanding via xslit imaging. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013. J. Yu and L. McMillan. General linear cameras. In European Conference on Computer Vision (ECCV), 2004. J. Yu, L. McMillan, and P. Sturm. Multi-perspective modelling, rendering and imaging. Computer Graphics Forum, 29(1):227–246, 2010. A. Zomet, D. Feldman, S. Peleg, and D. Weinshall. Mosaicing new views: the crossed-slits projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(6):741–754, June 2003.