nips nips2005 nips2005-23 nips2005-23-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: James Diebel, Sebastian Thrun
Abstract: This paper describes a highly successful application of MRFs to the problem of generating high-resolution range images. A new generation of range sensors combines the capture of low-resolution range images with the acquisition of registered high-resolution camera images. The MRF in this paper exploits the fact that discontinuities in range and coloring tend to co-align. This enables it to generate high-resolution, low-noise range images by integrating regular camera images into the range data. We show that by using such an MRF, we can substantially improve over existing range imaging technology. 1
[1] C.L. Bajaj and G. Xu. Anisotropic diffusion of surfaces and functions on surfaces. In Proceedings of SIGGRAPH, pages 4–32, 2003.
[2] S. Baker, R Szeliski, and P. Anandan. A layered approach to stereo reconstruction. In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), pages 434–438, Santa Barbara, CA, 1998.
[3] U. Clarenz, U. Diewald, and M. Rumpf. Anisotropic geometric diffusion in surface processing. In Proceedings of the IEEE Conference on Visualization, pages 397–405, 2000.
[4] J. Davis, R. Ramamoothi, and S. Rusinkiewicz. Spacetime stereo: A unifying framework for depth from triangulation. In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2003.
[5] M. Desbrun, M. Meyer, P. Schr¨ der, and A. Barr. Anisotropic feature-preserving denoising of o height fields and bivariate data. In Proceedings Graphics Interface, Montreal, Quebec, 2000.
[6] M. Desbrun, M. Meyer, P. Schr¨ der, and A. H. Barr. Implicit fairing of irregular meshes using o diffusion and curvature flow. In Proceedings of SIGGRAPH, 1999. ¨
[7] J. Diebel, S. Thrun, and M. Bruning. A bayesian method for probable surface reconstruction and decimation. IEEE Transactions on Graphics, 2005. To appear.
[8] M. Elad and A. Feuer. Restoration of single super-resolution image from several blurred. IEEE Transcation on Image Processing, 6(12):1646–1658, 1997.
[9] S. Fleishman, I. Drori, and D. Cohen-Or. Bilateral mesh denoising. In Proceedings of SIGGRAPH, pages 950–953, 2003.
[10] T.R. Jones, F. Durand, and M. Desbrun. Non-iterative, feature-preserving mesh smoothing. In Proceedings of SIGGRAPH, pages 943–949, 2003.
[11] I. K. Jung and S. Lacroix. High resolution terrain mapping using low altitude aerial stereo imagery. In Proceedings of the International Conference on Computer Vision (ICCV), Nice, France, 2003.
[12] W. H. Press. Numerical recipes in C: the art of scientific computing. Cambridge University Press, Cambridge; New York, 1988.
[13] S. Rusinkiewicz and M. Levoy. Efficient variants of the ICP algorithm. In Proc. Third International Conference on 3D Digital Imaging and Modeling (3DIM), Quebec City, Canada, 2001. IEEEComputer Society.
[14] D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1-3):7–42, 2002.
[15] J. Sun, H.-Y. Shum, and N.-N. Zheng. Stereo matching using belief propagation. IEEE Transcation on PAMI, 25(7), 2003.
[16] R. Szeliski. Stereo algorithms and representations for image-based rendering. In Proceedings of the British Machine Vision Conference, Vol 2, pages 314–328, 1999.
[17] G. Taubin. A signal processing approach to fair surface design. In Proceedings of SIGGRAPH, pages 351–358, 1995.
[18] S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics. MIT Press, Cambridge, MA, 2005.
[19] Y. Weiss and W.T. Freeman. Correctness of belief propagation in gaussian graphical models of arbitrary topology. Neural Computation, 13(10):2173–2200, 2001.
[20] W. T. Freeman and A. Torralba. Shape recipes: Scene representations that refer to the image. In Advances in Neural Information Processing Systems (NIPS) 15, Cambridge, MA, 2003. MIT Press.