Occlusions and binocular stereo
International Journal of Computer Vision
A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Variable Window Approach to Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Without Epipolar Lines: A Maximum-Flow Formulation
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Cooperative Algorithm for Stereo Matching and Occlusion Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Occlusions, Discontinuities, and Epipolar Lines in Stereo
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Efficient Stereo with Multiple Windowing
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Globally Optimal Regions and Boundaries
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
SMBV '01 Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV'01)
Modelling the environment of an exploring vehicle by means of stereo vision
Modelling the environment of an exploring vehicle by means of stereo vision
Fast Unambiguous Stereo Matching Using Reliability-Based Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time disparity map computation module
Microprocessors & Microsystems
Distinctive Similarity Measure for stereo matching under point ambiguity
Computer Vision and Image Understanding
Feature correspondence with constrained global spatial structures
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Extracting dense features for visual correspondence with graph cuts
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A real-time fuzzy hardware structure for disparity map computation
Journal of Real-Time Image Processing
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We present a new feature based algorithm for stereo correspondence. Most of the previous feature based methods match sparse features like edge pixels, producing only sparse disparity maps. Our algorithm detects and matches dense features between the left and right images of a stereo pair, producing a semi-dense disparity map. Our dense feature is defined with respect to both images of a stereo pair, and it is computed during the stereo matching process, not a preprocessing step. In essence, a dense feature is a connected set of pixels in the left image and a corresponding set of pixels in the right image such that the intensity edges on the boundary of these sets are stronger than their matching error (which is the difference in intensities between corresponding boundary pixels). Our algorithm produces accurate semi-dense disparity maps, leaving featureless regions in the scene unmatched. It is robust, requires little parameter tuning, can handle brightness differences between images, nonlinear errors, and is fast (linear complexity).