Robust regression and outlier detection
Robust regression and outlier detection
Comparison of the Efficiency of Deterministic and Stochastic Algorithms for Visual Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel and Deterministic Algorithms from MRFs: Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance Evaluation of Scene Registration and Stereo Matching for Artographic Feature Extraction
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A survey of image registration techniques
ACM Computing Surveys (CSUR)
Performance of optical flow techniques
International Journal of Computer Vision
A maximum likelihood stereo algorithm
Computer Vision and Image Understanding
Stereo Matching with Nonlinear Diffusion
International Journal of Computer Vision
Occlusions, Discontinuities, and Epipolar Lines in Stereo
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Disparity-Space Images and Large Occlusion Stereo
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Prediction Error as a Quality Metric for Motion and Stereo
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Efficient graph-based energy minimization methods in computer vision
Efficient graph-based energy minimization methods in computer vision
A Maximum-Flow Formulation of the N-Camera Stereo Correspondence Problem
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Depth from edge and intensity based stereo
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
What Energy Functions Can Be Minimized via Graph Cuts?
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Stereo Correspondence Using GA-Based Segmentation
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
Sharp and Dense Disparity Maps Using Multiple Windows
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A Comparative Study of Performance and Implementation of Some Area-Based Stereo Algorithms
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Multi-camera Scene Reconstruction via Graph Cuts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Statistical model for intensity differences of corresponding points between stereo image pairs
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Optimization by Stochastic Continuation
SIAM Journal on Imaging Sciences
A measure for accuracy disparity maps evaluation
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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While many algorithms for computing stereo correspondence have been proposed, there has been very little work on experimentally evaluating algorithm performance, especially using real (rather than synthetic) imagery. In this paper we propose an experimental comparison of several different stereo algorithms. We use real imagery, and explore two different methodologies, with different strengths and weaknesses. Our first methodology is based upon manual computation of dense ground truth. Here we make use of a two stereo pairs: one of these, from the University of Tsukuba, contains mostly fronto-parallel surfaces; while the other, which we built, is a simple scene with a slanted surface. Our second methodology uses the notion of prediction error, which is the ability of a disparity map to predict an (unseen) third image, taken from a known camera position with respect to the input pair. We present results for both correlation-style stereo algorithms and techniques based on global methods such as energy minimization. Our experiments suggest that the two methodologies give qualitatively consistent results. Source images and additional materials, such as the implementations of various algorithms, are available on the web from http://www.research.microsoft.com/~szeliski/stereo.