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.
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Landa-Becerra, R., de la Fraga, L.G. (2008). Triangulation Using Differential Evolution. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2008. Lecture Notes in Computer Science, vol 4974. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78761-7_38
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DOI: https://doi.org/10.1007/978-3-540-78761-7_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78760-0
Online ISBN: 978-3-540-78761-7
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