Abstract
This paper examines the relationship between iso-disparity contours in stereo disparity space and planar surfaces in the scene. We specify constraints that may be exploited to group iso-disparity contours belonging to the same planar surface, and identify discontinuities between planar surfaces. We demonstrate the use of such constraints for planar surface extraction, particularly where the boundaries between surfaces are orientation discontinuities rather than depth discontinuities (e.g., segmenting obstacles and walls from a ground plane). We demonstrate the advantages of our approach over a range of indoor and outdoor stereo images, and show that iso-disparity analysis can provide a robust and efficient means of segmenting smooth surfaces, and obtaining planar surface models.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bartoli, A.: A random sampling strategy for piecewise planar scene segmentation. Computer Vision and Image Understanding: CVIU 105, 42–59 (2007)
Okada, K., Kagami, S., Inaba, M., Inoue, H.: Plane segment finder: algorithm, implementation and applications. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), vol. 2, pp. 2120–2125 (2001)
Oh, J.D., Ma, S., Kuo, C.C.: Stereo matching via disparity estimation and surface modeling. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–8 (2007)
Hong, L., Chen, G.: Segment-based stereo matching using graph cuts. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. I–74–I–81 (2004)
Kolmogorov, V., Zabih, R.: Computing visual correspondence with occlusions using graph cuts. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), vol. 2, pp. 508–515 (2001)
Sinha, S.N., Steedly, D., Szeliski, R.: Piecewise planar stereo for image-based rendering. In: Proceedings of the IEEE International Conference on Computer Vision, ICCV (2009)
Se, S., Brady, M.: Stereo vision-based obstacle detection for partially sighted people. In: Chin, R., Pong, T.-C. (eds.) ACCV 1998. LNCS, vol. 1352. Springer, Heidelberg (1997)
Fischler, M.A., Bolles, R.C.: Random sample consensus: A paradigm for model fitting with application to image analysis and automated cartography. Communications of the ACM 24(6), 381–395 (1981)
Thakoor, N., Jung, S., Gao, J.: Real-time planar surface segmentation in disparity space. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–8 (2007)
Trucco, E., Isgro, F., Bracchi, F.: Plane detection in disparity space. In: International Conference on Visual Information Engineering, VIE 2003, pp. 73–76 (2003)
Pollefeys, M., Sinha, S.N.: Iso-disparity surfaces for general stereo configurations. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3023, pp. 509–520. Springer, Heidelberg (2004)
Fermüler, C., Aloimonos, Y.: On the geometry of visual correspondence. International Journal of Computer Vision 21, 223–247 (1997)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2000)
Cremers, D., Rousson, M., Deriche, R.: A review of statistical approaches to level set segmentation: Integrating color, texture, motion and shape. International Journal of Computer Vision 72, 215 (2007)
Hirschmler, H., Scharstein, D.: Evaluation of cost functions for stereo matching. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
McCarthy, C., Barnes, N. (2011). Surface Extraction from Iso-disparity Contours. In: Kimmel, R., Klette, R., Sugimoto, A. (eds) Computer Vision – ACCV 2010. ACCV 2010. Lecture Notes in Computer Science, vol 6495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19282-1_33
Download citation
DOI: https://doi.org/10.1007/978-3-642-19282-1_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19281-4
Online ISBN: 978-3-642-19282-1
eBook Packages: Computer ScienceComputer Science (R0)