Visual localisation from structureless rigid models

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Abstract

Visual rigid localisation algorithms can be described by their model/sensor input couple, where model and input can either be 2-D or 3-D sets of points. While Perspective-N-Point (PnP) solvers directly solve the 3-D/2-D case, to the best of our knowledge there is no localisation method to directly solve the 2-D/3-D case. This work proposes to handle the 2-D/3-D case by expressing it as two successive PnP problems which can be dealt with using classical solvers. Results suggest the overall method has comparable or better precision and robustness than state of the art PnP solvers. The approach is demonstrated on an object localisation application.

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APA

Manfredi, G., Devy, M., & Sidobre, D. (2015). Visual localisation from structureless rigid models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9386, pp. 510–520). Springer Verlag. https://doi.org/10.1007/978-3-319-25903-1_44

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