A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Multiple Stereo Matching Using an Extended Architecture
FPL '01 Proceedings of the 11th International Conference on Field-Programmable Logic and Applications
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Support-Weight Approach for Correspondence Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconfigurable hardware implementation of a phase-correlation stereoalgorithm
Machine Vision and Applications
Local Stereo Matching with Segmentation-based Outlier Rejection
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
An Introduction to 3D Computer Vision Techniques and Algorithms
An Introduction to 3D Computer Vision Techniques and Algorithms
A Real-Time Occlusion Aware Hardware Structure for Disparity Map Computation
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
Accurate hardware-based stereo vision
Computer Vision and Image Understanding
Towards hardware stereoscopic 3D reconstruction: a real-time FPGA computation of the disparity map
Proceedings of the Conference on Design, Automation and Test in Europe
Real-time stereo vision on a reconfigurable system
SAMOS'05 Proceedings of the 5th international conference on Embedded Computer Systems: architectures, Modeling, and Simulation
FPGA Design and Implementation of a Real-Time Stereo Vision System
IEEE Transactions on Circuits and Systems for Video Technology
Algorithm and Architecture of Disparity Estimation With Mini-Census Adaptive Support Weight
IEEE Transactions on Circuits and Systems for Video Technology
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Disparity estimation in stereoscopic vision is a vital step for the extraction of depth information from stereo images. This paper presents the hardware implementation of a disparity estimation system that enables good performance in both accuracy and speed. The architecture implements an adaptive support weight stereo correspondence algorithm, which integrates information obtained from image segmentation, in an attempt to increase the robustness of the matching process. The proposed system integrates optimization techniques that make the algorithm hardware-friendly and suitable for embedded vision systems. A prototype of the architecture was implemented on an FPGA, achieving 30 fps for 640x480 image sizes. The quality of the disparity maps generated by the proposed system is also better than other existing hardware implementations featuring fixed support local correspondence methods.