Depth Discontinuities by Pixel-to-Pixel Stereo
International Journal of Computer Vision
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Stereo Vision in Structured Environments by Consistent Semi-Global Matching
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
A robust approach for ego-motion estimation using a mobile stereo platform
IWCM'04 Proceedings of the 1st international conference on Complex motion
Belief-propagation on edge images for stereo analysis of image sequences
RobVis'08 Proceedings of the 2nd international conference on Robot vision
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
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Today's stereo vision algorithms and computing technology allow real-time 3D data analysis, for example for driver assistance systems. A recently developed Semi-Global Matching (SGM) approach by H. Hirschmüller became a popular choice due to performance and robustness. This paper evaluates different parameter settings for SGM, and its main contribution consists in suggesting to include a second order prior into the smoothness term of the energy function. It also proposes and tests a new cost function for SGM. Furthermore, some preprocessing (edge images) proved to be of great value for improving SGM stereo results on real-world sequences, as previously already shown by S. Guan and R. Klette for belief propagation. There is also a performance gain for engineered stereo data (e.g.) as currently used on the Middlebury stereo website. However, the fact that results are not as impressive as on the .enpeda.. sequences indicates that optimizing for engineered data does not neccessarily improve real world stereo data analysis.