The Infection Algorithm: An Artificial Epidemic Approach for Dense Stereo Correspondence

Authors:
Gustavo Olague;Francisco Fernández;Cynthia B. Pérez;Evelyne Lutton
Affiliations:
CICESE Research Center Applied Physics Division Centro de Investigación Científica y de Educación Superior de Ensenada, B.C. Km. 107 Carretera Tijuana-Ensenada 22860, Ensenada ...;Universidad de Extremadura Computer Science Department Centro Universitario de Merida C/Sta Teresa de Jornet, 38 06800 Merida, Spain;EvoVisión Laboratory CICESE Research Center Km. 107 Carretera Tijuana-Ensenada 22860, Ensenada, B.C. México;INRIA Rocquencourt Complex Team Domaine de Voluceau, BP 105 78153 Le Chesnay Cedex France Evelyne.Lutton@inria.fr
Venue:
Artificial Life
Year:
2006

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Abstract

We present a new bio-inspired approach applied to a problem of stereo image matching. This approach is based on an artificial epidemic process, which we call the infection algorithm. The problem at hand is a basic one in computer vision for 3D scene reconstruction. It has many complex aspects and is known as an extremely difficult one. The aim is to match the contents of two images in order to obtain 3D information that allows the generation of simulated projections from a viewpoint that is different from the ones of the initial photographs. This process is known as view synthesis. The algorithm we propose exploits the image contents in order to produce only the necessary 3D depth information, while saving computational time. It is based on a set of distributed rules, which propagate like an artificial epidemic over the images. Experiments on a pair of real images are presented, and realistic reprojected images have been generated.