International Journal of Computer Vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Dense Features for Semi-Dense Stereo Correspondence
International Journal of Computer Vision
Occlusions and Binocular Stereo
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Finding the Largest Unambiguous Component of Stereo Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Distinctiveness Maps for Image Matching
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Fast Stereo Matching Using Reliability-Based Dynamic Programming and Consistency Constraints
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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
Estimate Large Motions Using the Reliability-Based Motion Estimation Algorithm
International Journal of Computer Vision
Real-time disparity map computation module
Microprocessors & Microsystems
Search Space Reduction for MRF Stereo
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
A Real-Time Occlusion Aware Hardware Structure for Disparity Map Computation
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Image and Vision Computing
Stereo depth estimation using synchronous optimization with segment based regularization
Pattern Recognition Letters
A real-time fuzzy hardware structure for disparity map computation
Journal of Real-Time Image Processing
An effective stereo matching algorithm with optimal path cost aggregation
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Real-time architecture for a robust multi-scale stereo engine on FPGA
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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An efficient unambiguous stereo matching technique is presented in this paper. Our main contribution is to introduce a new reliability measure to dynamic programming approaches in general. For stereo vision application, the reliability of a proposed match on a scanline is defined as the cost difference between the globally best disparity assignment that includes the match and the globally best assignment that does not include the match. A reliability-based dynamic programming algorithm is derived accordingly, which can selectively assign disparities to pixels when the corresponding reliabilities exceed a given threshold. The experimental results show that the new approach can produce dense (70 percent of the unoccluded pixels) and reliable (error rate