International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Finding the Largest Unambiguous Component of Stereo Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator
FCRC '96/WACG '96 Selected papers from the Workshop on Applied Computational Geormetry, Towards Geometric Engineering
Markov Random Fields with Efficient Approximations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Adaptive Support-Weight Approach for Correspondence Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Computer Vision and Image Understanding
Stereo Processing by Semiglobal Matching and Mutual Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Search Space Reduction for MRF Stereo
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Global Stereo Reconstruction under Second-Order Smoothness Priors
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-quality single-shot capture of facial geometry
ACM SIGGRAPH 2010 papers
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Real time vision based multi-person tracking for mobile robotics and intelligent vehicles
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
Continuous markov random fields for robust stereo estimation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Taking mobile multi-object tracking to the next level: people, unknown objects, and carried items
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Stixels motion estimation without optical flow computation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Robust 3D human face reconstruction by consumer binocular-stereo cameras
Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry
Two-frame stereo photography in low-light settings: a preliminary study
Proceedings of the 9th European Conference on Visual Media Production
How to localize humanoids with a single camera?
Autonomous Robots
Robust object tracking in crowd dynamic scenes using explicit stereo depth
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Iterative semi-global matching for robust driver assistance systems
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Stereo reconstruction and contrast restoration in daytime fog
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
Shift-Map based stereo image retargeting with disparity adjustment
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
International Journal of Computer Vision
Frequency-based underwater terrain segmentation
Autonomous Robots
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In this paper we propose a novel approach to binocular stereo for fast matching of high-resolution images. Our approach builds a prior on the disparities by forming a triangulation on a set of support points which can be robustly matched, reducing the matching ambiguities of the remaining points. This allows for efficient exploitation of the disparity search space, yielding accurate dense reconstruction without the need for global optimization. Moreover, our method automatically determines the disparity range and can be easily parallelized. We demonstrate the effectiveness of our approach on the large-scale Middlebury benchmark, and show that state-of-the-art performance can be achieved with significant speedups. Computing the left and right disparity maps for a one Megapixel image pair takes about one second on a single CPU core.