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Colored Point Cloud Registration Revisited

Cited 175 time in Web of Science Cited 233 time in Scopus
Authors

Park, Jaesik; Zhou, Qian-Yi; Koltun, Vladlen

Issue Date
2017
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
Proceedings of the IEEE International Conference on Computer Vision, Vol.2017-October, pp.143-152
Abstract
We present an algorithm for 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 precision of the resulting system is demonstrated on real-world scenes with accurate ground-truth models.
ISSN
1550-5499
URI
https://hdl.handle.net/10371/201319
DOI
https://doi.org/10.1109/ICCV.2017.25
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  • College of Engineering
  • Dept. of Computer Science and Engineering
Research Area Computer Graphics, Computer Vision, Machine Learning

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