A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
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
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
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
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
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
Multi-View Stereo Reconstruction and Scene Flow Estimation with a Global Image-Based Matching Score
International Journal of Computer Vision
Poisson surface reconstruction
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
SBA: A software package for generic sparse bundle adjustment
ACM Transactions on Mathematical Software (TOMS)
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-quality single-shot capture of facial geometry
ACM SIGGRAPH 2010 papers
Accurate, Dense, and Robust Multiview Stereopsis
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
High-quality shape from multi-view stereo and shading under general illumination
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Object stereo -- Joint stereo matching and object segmentation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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We propose a binocular stereo method which is optimized for reconstructing surface detail and exploits the high image resolutions of current digital cameras. Our method occupies a middle ground between stereo algorithms focused on depth layering of cluttered scenes and multi-view ''object reconstruction'' approaches which require a higher view count. It is based on global non-linear optimization of continuous scene depth rather than discrete pixel disparities. We propose a mesh-based data-term for large images, and a smoothness term using robust error norms to allow detailed surface geometry. We show that the continuous optimization approach enables interesting extensions beyond the core algorithm: Firstly, with small changes to the data-term camera parameters instead of depth can be optimized in the same framework. Secondly, we argue that our approach is well suited for a semi-interactive reconstruction work-flow, for which we propose several tools.