Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
A Multigrid Approach for Hierarchical Motion Estimation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Multigrid Approach for Hierarchical Motion Estimation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Adaptive Grid Refinement Procedures for Efficient Optical Flow Computation
International Journal of Computer Vision
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
International Journal of Computer Vision
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Dense estimation and object-based segmentation of the optical flow with robust techniques
IEEE Transactions on Image Processing
A fast stereo matching algorithm suitable for embedded real-time systems
Computer Vision and Image Understanding
Real-time high-definition stereo matching on FPGA
Proceedings of the 19th ACM/SIGDA international symposium on Field programmable gate arrays
Real-time stereo on GPGPU using progressive multi-resolution adaptive windows
Image and Vision Computing
Using active illumination for accurate variational space-time stereo
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
A precise real-time stereo algorithm
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Intelligent data analysis by a home-use human monitoring robot
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
Cost volume-based interactive depth editing in stereo post-processing
Proceedings of the 10th European Conference on Visual Media Production
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Estimating the disparity field between two stereo images is a common task in computer vision, e.g., to determine a dense depth map. Variational methods currently are among the most accurate techniques for dense disparity map reconstruction. In this paper a multi-level adaptive technique is combined with a multigrid approach that allows the variational method to achieve real-time performance (on a CPU). The multi-level adaptive technique refines the grid only at peculiarities in the solution. Thereby it reduces the computational effort and ensures that the reconstruction quality is kept almost the same. Further, we introduce a technique that adapts the regularizer, used in the variational approach, dependend on the the current state of the optimization. This improves the reconstruction quality. Our real-time approach is evaluated on standard datasets and it is shown to perform better than other real-time disparity estimation approaches.