Stereo Without Epipolar Lines: A Maximum-Flow Formulation
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Markov Random Fields with Efficient Approximations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Illumination-Invariant Tracking via Graph Cuts
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Image and depth from a conventional camera with a coded aperture
ACM SIGGRAPH 2007 papers
International Journal of Computer Vision
Robust Stereo Matching Using Adaptive Normalized Cross-Correlation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient large-scale stereo matching
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An intensity similarity measure in low-light conditions
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
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Image-pairs captured from a rig of two, carefully arranged cameras are increasingly used to reconstruct partial 3D information. A crucial step in this reconstruction is the matching of points in the two images that are projections of the same 3D point through each camera. Despite receiving much attention, algorithms to match correspondencing points in two-frame stereo images are both slow, as well as surprisingly fragile. The problem is exacerbated by noise or blur in the input images because of the potential ambiguities they introduce in the matching process. For scenes that are poorly illuminated, it is necessary to make a combination of three adjustments: To increase the size of the aperture to allow more light; to increase the duration of exposure; and to increase the sensor-gain (ISO). These adjustments potentially introduce defocus, motion blur and noise --- all of which adversely affect reconstruction. We present an exploratory study of how they relatively affect stereo-correspondence algorithms by comparing the accuracy and precision of three reconstruction algorithms over the space of exposures.