UAV-Based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction
Abstract
In this paper we present an autonomous system for acquiring close-range high-resolution images that maximize the quality of a later-on 3D reconstruction with respect to coverage, ground resolution and 3D uncertainty. In contrast to previous work, our system uses the already acquired images to predict the confidence in the output of a dense multi-view stereo approach without executing it. This confidence encodes the likelihood of a successful reconstruction with respect to the observed scene and potential camera constellations. Our prediction module runs in real-time and can be trained without any externally recorded ground truth. We use the confidence prediction for on-site quality assurance and for planning further views that are tailored for a specific multi-view stereo approach with respect to the given scene. We demonstrate the capabilities of our approach with an autonomous Unmanned Aerial Vehicle (UAV) in a challenging outdoor scenario.
Cite
Text
Mostegel et al. "UAV-Based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016. doi:10.1109/CVPRW.2016.8Markdown
[Mostegel et al. "UAV-Based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016.](https://mlanthology.org/cvprw/2016/mostegel2016cvprw-uavbased/) doi:10.1109/CVPRW.2016.8BibTeX
@inproceedings{mostegel2016cvprw-uavbased,
title = {{UAV-Based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction}},
author = {Mostegel, Christian and Rumpler, Markus and Fraundorfer, Friedrich and Bischof, Horst},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2016},
pages = {1-10},
doi = {10.1109/CVPRW.2016.8},
url = {https://mlanthology.org/cvprw/2016/mostegel2016cvprw-uavbased/}
}