Novel dense matching algorithm with voronoi decomposition of images

A novel dense stereo matching algorithm based on propagation within a Voronoi decomposition of the image plane is proposed. A weighted sum of squared differences is developed as the cost function. The size of the window is adaptive; it is set in inverse proportion to the texture density inside it for reliable propagation. A simple way to detect possible areas of depth discontinuities is developed to determine the search regions. A significant merit of the algorithm is that it can be applied to a wide variety of images, including those with large disparities, with or without rectification. It has been verified on real images, with satisfactory results.

[1]  Masatoshi Okutomi,et al.  A Simple Stereo Algorithm to Recover Precise Object Boundaries and Smooth Surfaces , 2004, International Journal of Computer Vision.

[2]  Vladimir Kolmogorov,et al.  An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision , 2004, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Long Quan,et al.  Quasi-Dense Reconstruction from Image Sequence , 2002, ECCV.

[4]  Ye Zhang,et al.  Stereo Matching with Segmentation-Based Cooperation , 2002, ECCV.

[5]  Richard Szeliski,et al.  Symmetric Sub-Pixel Stereo Matching , 2002, ECCV.

[6]  Maxime Lhuillier,et al.  Efficient Dense Matching for Textured Scenes using Region Growing , 1998, BMVC.

[7]  Richard Szeliski,et al.  Stereo Matching with Nonlinear Diffusion , 1998, International Journal of Computer Vision.

[8]  Takeo Kanade,et al.  Stereo by Intra- and Inter-Scanline Search Using Dynamic Programming , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[10]  Takeo Kanade,et al.  A Cooperative Algorithm for Stereo Matching and Occlusion Detection , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Darius Burschka,et al.  Advances in Computational Stereo , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Takeo Kanade,et al.  A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Laurent Moll,et al.  Real time correlation-based stereo: algorithm, implementations and applications , 1993 .

[14]  M. Vergauwen,et al.  A hierarchical stereo algorithm using dynamic programming , 2001, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001).

[15]  Maarten Vergauwen,et al.  A Hierarchical Symmetric Stereo Algorithm Using Dynamic Programming , 2002, International Journal of Computer Vision.

[16]  Yee-Hong Yang,et al.  Multi-resolution stereo matching using genetic algorithm , 2001, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001).

[17]  Ingemar J. Cox,et al.  A maximum-flow formulation of the N-camera stereo correspondence problem , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[18]  Aaron F. Bobick,et al.  Large Occlusion Stereo , 1999, International Journal of Computer Vision.

[19]  Nanning Zheng,et al.  Stereo Matching Using Belief Propagation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..