Computer
On Three-Dimensional Surface Reconstruction Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Surface Description from Binocular Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object-centered surface reconstruction: combining multi-image stereo and shading
International Journal of Computer Vision
Stereo Matching with Nonlinear Diffusion
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
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
Non-parametric Local Transforms for Computing Visual Correspondence
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
SIGGRAPH '78 Proceedings of the 5th annual conference on Computer graphics and interactive techniques
Visual Correspondence Using Energy Minimization and Mutual Information
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Automatic Augmentation and Meshing of Sparse 3D Scene Structure
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Surface Reconstruction from Stereo Data Using a Three-Dimensional Markov Random Field Model
IEICE - Transactions on Information and Systems
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Stereo by Intra- and Inter-Scanline Search Using Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reliability analysis of the rank transform for stereo matching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Surfaces with occlusions from layered stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Modeling the world in three dimensions has been attracting a growing interest both in applications and science. In many cases, such 3D models are achieved by triangulating corresponding features recorded by several images of the same field taken from different points of view. This, however, requires the ability to match corresponding image elements detected in different images. In this paper, an algorithm for stereo matching in noisy pairs of outdoor images is described. The proposed algorithm applies a standard window-based correlation, but uses a fuzzy logic-based similarity function that models the HSV color space. This fuzzy logic modeling allows a robust color comparison that can tolerate a certain degree of changes in the illumination conditions and can be used for finding corresponding pixels in noisy sets of images. While the proposed algorithm does not introduce an improvement over existing methods in ideal conditions, experiments suggest that it provides significantly better results when the images in the set are relatively different from each other, and can be effective for matching corresponding features in images taken in different weather conditions, different positions of the sun, different optics or other real-life situations in which pinhole conditions are not available.