Abstract
This paper addresses multiple-view L 2 triangulation by proposing a new method based on eigenvalue problems (EVPs), which belong to the class of convex programming. The proposed method provides a candidate of the sought 3D point and a straightforward condition for establishing its optimality, which also yields a guaranteed range for the optimal cost of the triangulation problem in case of non-optimality. The proposed method is illustrated through some well-known examples with real data, for which the provided candidate 3D point is always optimal. These examples also show that the computational time of the proposed method is indeed small and competitive with existing approaches.
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Chesi, G., Hung, Y.S. (2010). EVP-Based Multiple-View Triangulation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17277-9_12
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DOI: https://doi.org/10.1007/978-3-642-17277-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17276-2
Online ISBN: 978-3-642-17277-9
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