Abstract : Thermal imaging has become a valuable tool in various fields for remote sensing and can provide relevant information to perform object recognition or classification. In this paper, we present an automated method to obtain a 3D model fusing data from a visible and a thermal camera. The RGB and thermal point clouds are generated independently by structure from motion. The registration process includes a normalization of the point cloud scale, a global registration based on calibration data and the output of the structure from motion, and a fine registration employing a variant of the Iterative Closest Point optimization. Experimental results demonstrate the accuracy and robustness of the overall process.
Type de document :
Communication dans un congrès
Multi-Sensor Fusion for Dynamic Scene Understanding, Oct 2017, Venice, Italy
https://hal-upec-upem.archives-ouvertes.fr/hal-01625092
Contributeur : Vincent Nozick
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Soumis le : vendredi 27 octobre 2017 - 10:33:42
Dernière modification le : jeudi 22 novembre 2018 - 14:39:42
Document(s) archivé(s) le : dimanche 28 janvier 2018 - 12:30:26
Trong Truong, Masahiro Yamaguchi, Shohei Mori, Vincent Nozick, Hideo Saito. Registration of RGB and thermal point clouds generated by structure from motion. Multi-Sensor Fusion for Dynamic Scene Understanding, Oct 2017, Venice, Italy. 〈hal-01625092〉
