Performance of optical flow techniques
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Spatio-Temporal Stereo Using Multi-Resolution Subdivision Surfaces
International Journal of Computer Vision
Real-Time Correlation-Based Stereo Vision with Reduced Border Errors
International Journal of Computer Vision
Motion - Stereo Integration for Depth Estimation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
A Stereo Machine for Video-Rate Dense Depth Mapping and Its New Applications
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Variational Stereovision and 3D Scene Flow Estimation with Statistical Similarity Measures
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
An Energy Minimisation Approach to Stereo-Temporal Dense Reconstruction
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Real-Time Stereo by using Dynamic Programming
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 3 - Volume 03
Improved Real-Time Stereo on Commodity Graphics Hardware
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 3 - Volume 03
Spacetime Stereo: A Unifying Framework for Depth from Triangulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-Scale 3D Scene Flow from Binocular Stereo Sequences
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Image-Gradient-Guided Real-Time Stereo on Graphics Hardware
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Near Real-Time Reliable Stereo Matching Using Programmable Graphics Hardware
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A GPU-based Algorithm for Estimating 3D Geometry and Motion in Near Real-time
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Enforcing temporal consistency in real-time stereo estimation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Real-Time Stereo Matching Using Orthogonal Reliability-Based Dynamic Programming
IEEE Transactions on Image Processing
Stereoscopic Scene Flow Computation for 3D Motion Understanding
International Journal of Computer Vision
On the evaluation of scene flow estimation
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
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Disparity flow depicts the 3D motion of a scene in the disparity space of a given view and can be considered as view-dependent scene flow. A novel algorithm is presented to compute disparity maps and disparity flow maps in an integrated process. Consequently, the disparity flow maps obtained helps to enforce the temporal consistency between disparity maps of adjacent frames. The disparity maps found also provides the spatial correspondence information that can be used to cross-validate disparity flow maps of different views. Two different optimization approaches are integrated in the presented algorithm for searching optimal disparity values and disparity flows. The local winner-take-all approach runs faster, whereas the global dynamic programming based approach produces better results. All major computations are performed in the image space of the given view, leading to an efficient implementation on programmable graphics hardware. Experimental results on captured stereo sequences demonstrate the algorithm's capability of estimating both 3D depth and 3D motion in real-time. Quantitative performance evaluation using synthetic data with ground truth is also provided.