Triangulation using differential evolution

Authors:
Ricardo Landa-Becerra;Luis G. De La Fraga
Affiliations:
Cinvestav, Computer Science Department, Mexico City, Mexico;Cinvestav, Computer Science Department, Mexico City, Mexico
Venue:
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Year:
2008

Citing 5
Cited 0

Triangulation

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An introduction to differential evolution

New ideas in optimization
Multiple View Geometry in Computer Vision

Multiple View Geometry in Computer Vision
Guiding single-objective optimization using multi-objective methods

EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

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Abstract

Triangulation is one step in Computer Vision where the 3D points are calculated from 2D point correspondences over 2D images. When these 2D points are free of noise, the triangulation is the intersection point of two lines, but in the presence of noise this intersection does not occur and then the best solution must be estimated. We propose in this article a fast algorithm that uses Differential Evolution to calculate the optimal triangulation.