Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
International Journal of Computer Vision
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Real-Time Systems: Design Principles for Distributed Embedded Applications
Real-Time Systems: Design Principles for Distributed Embedded Applications
Digital Image Processing
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Detecting Binocular Half-Occlusions: Empirical Comparisons of Five Approaches
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment
IEEE Transactions on Pattern Analysis and Machine Intelligence
What Energy Functions Can Be Minimized via Graph Cuts?
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Dense Stereo Correspondence Using Polychromatic Block Matching
CAIP '93 Proceedings of the 5th International Conference on Computer Analysis of Images and Patterns
Robust Dense Matching Using Local and Global Geometric Constraints
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation
SMBV '01 Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV'01)
Comparison of Graph Cuts with Belief Propagation for Stereo, using Identical MRF Parameters
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Binocular Helmholtz Stereopsis
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Neural adaptive stereo matching
Pattern Recognition Letters
A Dense Stereo Matching Using Two-Pass Dynamic Programming with Generalized Ground Control Points
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Shape and the Stereo Correspondence Problem
International Journal of Computer Vision
A Real-Time Large Disparity Range Stereo-System using FPGAs
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Adaptive Support-Weight Approach for Correspondence Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Stereo Matching with Segmentation-based Outlier Rejection
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Low-Cost Stereo Vision on an FPGA
FCCM '07 Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dense Two-Frame Stereo Correspondence by Self-organizing Neural Network
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Segmentation-based adaptive support for accurate stereo correspondence
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
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
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We propose in this paper a new method for real-time dense disparity map computing using a stereo pair of rectified images. Based on the neural network and Disparity Space Image (DSI) data structure, the disparity map computing consists of two main steps: initial disparity map estimation by combining the neuronal network and the DSI structure, and its refinement. Four improvements are introduced so that an accurate and fast result will be reached. The first one concerns the proposition of a new strategy in order to optimize the computation time of the initial disparity map. In the second one, a specific treatment is proposed in order to obtain more accurate disparity for the neighboring pixels to boundaries. The third one, it concerns the pixel similarity measure for matching score computation and it consists of using in addition to the traditional pixel intensities, the magnitude and orientation of the gradients providing more accuracy. Finally, the processing time of the method has been decreased consequently to our implementation of some critical steps on FPGAs. Experimental results on real datasets are conducted and a comparative evaluation of the obtained results relative to the state-of-art methods is presented.