Registration of RGB and Thermal Point Clouds Generated by Structure From Motion

Trong Phuc Truong, Masahiro Yamaguchi, Shohei Mori, Vincent Nozick, Hideo Saito; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017, pp. 419-427

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.

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[bibtex]
@InProceedings{Truong_2017_ICCV,
author = {Phuc Truong, Trong and Yamaguchi, Masahiro and Mori, Shohei and Nozick, Vincent and Saito, Hideo},
title = {Registration of RGB and Thermal Point Clouds Generated by Structure From Motion},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2017}
}