Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Matching with Nonlinear Diffusion
International Journal of Computer Vision
Reliable Estimation of Dense Optical Flow Fields with Large Displacements
International Journal of Computer Vision
Level Set Methods and the Stereo Problem
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-Frame Wide Baseline Matching
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph based algorithms for scene reconstruction from two or more views
Graph based algorithms for scene reconstruction from two or more views
Pattern Recognition Letters
Increasing efficiency in disparity calculation
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
An edge-guided image interpolation algorithm via directional filtering and data fusion
IEEE Transactions on Image Processing
Real-Time Stereo Matching Using Orthogonal Reliability-Based Dynamic Programming
IEEE Transactions on Image Processing
On-chip semidense representation map for dense visual features driven by attention processes
Journal of Real-Time Image Processing
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We describe a novel method for propagating disparity values using directional masks and a voting scheme. The driving force of the propagation direction is image gradient, making the process anisotropic, whilst ambiguities between propagated values are resolved using a voting scheme. This kind of anisotropic densification process achieves significant density enhancement at a very low error cost: in some cases erroneous disparities are voted out, resulting not only in a denser but also a more accurate final disparity map. Due to the simplicity of the method it is suitable for embedded implementation and can also be included as part of a system-on-chip (SOC). Therefore, it can be of great interest to the sector of the machine vision community that deals with embedded and/or real-time applications.