Colored Point Cloud Registration Revisited

Jaesik Park, Qian-Yi Zhou, Vladlen Koltun; The IEEE International Conference on Computer Vision (ICCV), 2017, pp. 143-152

Abstract


We present an algorithm for tightly aligning two colored point clouds. The key idea is to optimize a joint photometric and geometric objective that locks the alignment along both the normal direction and the tangent plane. We extend a photometric objective for aligning RGB-D images to point clouds, by locally parameterizing the point cloud with a virtual camera. Experiments demonstrate that our algorithm is more accurate and more robust than prior point cloud registration algorithms, including those that utilize color information. We use the presented algorithms to enhance a state-of-the-art scene reconstruction system. The accuracy of the resulting system is demonstrated on real-world scenes with accurate ground-truth models.

Related Material


[pdf]
[bibtex]
@InProceedings{Park_2017_ICCV,
author = {Park, Jaesik and Zhou, Qian-Yi and Koltun, Vladlen},
title = {Colored Point Cloud Registration Revisited},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {Oct},
year = {2017}
}