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

• Published in: Artificial life Vol. 12; no. 4; pp. 593 - 615
• Main Authors: Olague, Gustavo, Fernández, Francisco, Pérez, Cynthia B., Lutton, Evelyne
• Format: Journal Article
• Language: English
• Published: One Rogers Street, Cambridge, MA 02142-1209, USA MIT Press 01.10.2006
• Subjects: Algorithms; artificial epidemics; Artificial Intelligence; Computer Simulation; Depth Perception; Disease Outbreaks; epipolar geometry; Humans; Image matching; Image Processing, Computer-Assisted; Infection - epidemiology; infection algorithm; Photogrammetry; stereo vision
• ISSN: 1064-5462; 1530-9185
• DOI: 10.1162/artl.2006.12.4.593

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 . 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.