Aggregation of color information in stereo matching problem: a comparison study

Authors:
Mikel Galar;Miguel Pagola;Edurne Barrenechea;Carlos López-Molina;Humberto Bustince
Affiliations:
Universidad Pública de Navarra, Pamplona, Spain;Universidad Pública de Navarra, Pamplona, Spain;Universidad Pública de Navarra, Pamplona, Spain;Universidad Pública de Navarra, Pamplona, Spain;Universidad Pública de Navarra, Pamplona, Spain
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Year:
2010

Citing 4
Cited 0

A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

International Journal of Computer Vision
Non-parametric Local Transforms for Computing Visual Correspondence

ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Measures Based on Fuzzy Similarity for Stereo Matching of Color Images

Soft Computing - A Fusion of Foundations, Methodologies and Applications
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present a comparison study between different aggregation functions used in stereo matching problem. We add color information from images to the stereo matching algorithm by aggregating the similarities of the RGB channels which are calculated independently. We compare the accuracy of different stereo matching algorithms when using different aggregation functions. We show experimentally that the best function to use depends on the stereo matching algorithm considered.