Robust Real-Time 3D Modeling of Static Scenes Using Solely a Time-of-Flight Sensor
Abstract
An algorithm is proposed for the 3D modeling of static scenes solely based on the range and intensity data acquired by a time-of-flight camera during an arbitrary movement. No additional scene acquisition devices, like inertia sensor, positioning robots or intensity based cameras are incorporated. The current pose is estimated by maximizing the uncentered correlation coefficient between edges detected in the current and a preceding frame at a minimum frame rate of four fps and an average accuracy of 45 mm. The paper also describes several extensions for robust registration like multiresolution hierarchies and projection Iterative Closest Point algorithm. The basic registration algorithm and its extensions were intensively evaluated against ground truth data to validate the accuracy, robustness and real-time-capability.
Cite
Text
Feulner et al. "Robust Real-Time 3D Modeling of Static Scenes Using Solely a Time-of-Flight Sensor." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009. doi:10.1109/CVPRW.2009.5205204Markdown
[Feulner et al. "Robust Real-Time 3D Modeling of Static Scenes Using Solely a Time-of-Flight Sensor." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009.](https://mlanthology.org/cvprw/2009/feulner2009cvprw-robust/) doi:10.1109/CVPRW.2009.5205204BibTeX
@inproceedings{feulner2009cvprw-robust,
title = {{Robust Real-Time 3D Modeling of Static Scenes Using Solely a Time-of-Flight Sensor}},
author = {Feulner, Johannes and Penne, Jochen and Kollorz, Eva N. K. and Hornegger, Joachim},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2009},
pages = {74-81},
doi = {10.1109/CVPRW.2009.5205204},
url = {https://mlanthology.org/cvprw/2009/feulner2009cvprw-robust/}
}