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EVOW
2005
Springer

An Evolutionary Infection Algorithm for Dense Stereo Correspondence

10 years 8 months ago
An Evolutionary Infection Algorithm for Dense Stereo Correspondence
This work presents an evolutionary approach to improve the infection algorithm to solve the problem of dense stereo matching. Dense stereo matching is used for 3D reconstruction in stereo vision in order to achieve fine texture detail about a scene. The algorithm presented in this paper incorporates two different epidemic automata applied to the correspondence of two images. These two epidemic automata provide two different behaviours which construct a different matching. Our aim is to provide with a new strategy inspired on evolutionary computation, which combines the behaviours of both automata into a single correspondence process. The new algorithm will decide which epidemic automata to use based on inheritance and mutation, as well as the attributes, texture and geometry, of the input images. Finally, we show experiments in a real stereo pair to show how the new algorithm works.
Cynthia B. Pérez, Gustavo Olague, Francisco
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where EVOW
Authors Cynthia B. Pérez, Gustavo Olague, Francisco Fernández, Evelyne Lutton
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