Partial 3D Reconstruction using Evolutionary Algorithms

When reconstructing a scenario, it is necessary to know the structure of the elements present on the scene to have an interpretation. In this work we link 3D scenes reconstruction to evolutionary algorithms through the vision stereo theory. We consider vision stereo as a method that provides the reconstruction of a scene using only a couple of images of the scene and performing some computation. Through several images of a scene, captured from different positions, vision stereo can give us an idea about the threedimensional characteristics of the world. Vision stereo usually requires of two cameras, making an analogy to the mammalian vision system. In this work we employ only a camera, which is translated along a path, capturing images every certain distance. As we can not perform all computations required for an exhaustive reconstruction, we employ an evolutionary algorithm to partially reconstruct the scene in real time. The algorithm employed is the fly algorithm, which employ “flies" to reconstruct the principal characteristics of the world following certain evolutionary rules.

Authors:

• Mónica Pérez-Meza
• Rodrigo Montúfar-Chaveznava

Keywords:

• 3D Reconstruction
• Computer Vision
• EvolutionaryAlgorithms
• Vision Stereo.

References:

[1] Louchet, J. September 2000. "Stereo analysis using individual evolution
strategy". International conference on pattern recognition. Barcelona.
[2] Boumaza, A. M., Louchet, J. 2001. "Dynamic Flies: Using Real-Time
Parisian Evolution in Robotics". EvoWorkshops, pp.. 288-297.
[3] Louchet, J., Guyon, M., Lesot, M.-J., Boumaza, A. 2002, "Dynamic
Flies : a new pattern recognition tool applied to stereo sequence
processing", Pattern Recognition Letters, No. 23 pp. 335-345.