Abstract
This paper presents a system for dense area based disparity estimation from binocular rectified image sequences with the integration of temporal evidence. The system is using dense 2D optical flow fields and timely displaced disparity estimates to reason about the observed 3D scene flow. This scene flow is then exploited to strengthen timely consistent observations in the disparity estimation. Moreover a novel neighborhood assumption is presented, which allows to seamlessly implement the presented algorithm on the GPU. It is shown that by means of the presented approach the sensitivity to noise and ambiguities observed with plain real-time disparity estimations can be improved, even in fully dynamic scenarios with simultaneous movement of objects and cameras.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Yang, R., Pollefeys, M.: Multi-Resolution Real-Time Stereo on Commodity Graphics Hardware. In: Conference on Computer Vision and Pattern Recognition (CVPR 2003), Madison, Wisconsin, USA (June 2003)
Zhang, Y., Kambhamettu, C.: On 3d scene flow and structure estimation. In: 2001 Conference on Computer Vision and Pattern Recognition (CVPR 2001), December 2001, pp. 778–785 (2001)
Huguet, F., Devernay, F.: A variational method for scene flow estimation from stereo sequences. In: ICCV 2007, pp. 1–7 (2007)
Vedula, S., Baker, S.: Three-dimensional scene flow. IEEE Trans. Pattern Anal. Mach. Intell 27(3), 475–480 (2005); Member-Peter Rander and Member-Robert Collins and Fellow-Takeo Kanade
Leung, C., Appleton, B., Lovell, B.C., Sun, C.: An energy minimisation approach to stereo-temporal dense reconstruction. In: ICPR 2004: Proceedings of the Pattern Recognition, 17th International Conference on (ICPR 2004), Washington, DC, USA, vol. 4, pp. 72–75. IEEE Computer Society, Los Alamitos (2004)
Matthies, L., Kanade, T., Szeliski, R.: Kalman filter-based algorithms for estimating depth from image sequences. International Journal of Computer Vision 3(3), 209–238 (1989)
Badino, H., Franke, U., Mester, R.: Free space computation using stochastic occupancy grids and dynamic programming. In: Workshop on Dynamical Vision, ICCV (2007)
Gong, M.: Enforcing temporal consistency in real-time stereo estimation. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954, pp. 564–577. Springer, Heidelberg (2006)
Scharstein, D., Szeliski, R., Zabih, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. In: Proceedings of IEEE Workshop on Stereo and Multi-BaselineVision, Kauai, Hawaii (December 2001)
Collins, R.T.: A space-sweep approach to true multi-image matching. In: Proc. Computer Vision and Pattern Recognition Conf., pp. 358–363 (1996)
Scharstein, D., Szeliski, R.: Stereo matching with non-linear diffusion. International Journal of Computer Vision 28(2), 155 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bartczak, B., Jung, D., Koch, R. (2008). Real-Time Neighborhood Based Disparity Estimation Incorporating Temporal Evidence. In: Rigoll, G. (eds) Pattern Recognition. DAGM 2008. Lecture Notes in Computer Science, vol 5096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69321-5_16
Download citation
DOI: https://doi.org/10.1007/978-3-540-69321-5_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69320-8
Online ISBN: 978-3-540-69321-5
eBook Packages: Computer ScienceComputer Science (R0)