This paper addresses multiple-view L2 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. © 2010 Springer-Verlag.
CITATION STYLE
Chesi, G., & Hung, Y. S. (2010). EVP-based multiple-view triangulation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6455 LNCS, pp. 109–118). https://doi.org/10.1007/978-3-642-17277-9_12
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