Multiple view geometry in computer vision
Multiple view geometry in computer vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-camera Scene Reconstruction via Graph Cuts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
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
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Inclusion of a Second-Order Prior into Semi-Global Matching
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Belief Propagation for Stereo Analysis of Night-Vision Sequences
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Residual Images Remove Illumination Artifacts!
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Dynamic Programming Stereo on Real-World Sequences
Advances in Neuro-Information Processing
New Lane Model and Distance Transform for Lane Detection and Tracking
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Stereo by two-level dynamic programming
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Exact optimization for Markov random fields with convex priors
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Applying computer technology, such as computer vision in driver assistance, implies that processes and data are modeled as being discretized rather than being continuous. The area of stereo vision provides various examples how concepts known in discrete mathematics (e.g., pixel adjacency graphs, belief propagation, dynamic programming, max-flow/min-cut, or digital straight lines) are applied when aiming for efficient and accurate pixel correspondence solutions. The paper reviews such developments for a reader in discrete mathematics who is interested in applied research (in particular, in vision-based driver assistance). As a second subject, the paper also discusses lane detection and tracking, which is a particular task in driver assistance; recently the Euclidean distance transform proved to be a very appropriate tool for obtaining a fairly robust solution.