基于无人机自主图像采集与通过置信度预测的多视立体质量保障
计算机视觉与模式识别
2016-05-09 v1 机器人学
摘要
本文提出一种自主系统，用于获取近程高分辨率图像，以在覆盖度、地面分辨率和三维不确定性方面最大化后续三维重建的质量。与先前工作相反，我们的系统利用已获取的图像来预测密集多视立体方法输出的置信度，而无需执行该方法。该置信度编码了针对观测场景和潜在相机构型成功重建的可能性。我们的预测模块实时运行，且无需任何外部记录的 ground truth 即可训练。我们将置信度预测用于现场质量保障，以及针对给定场景规划专为特定多视立体方法定制的进一步视角。我们在一具有挑战性的户外场景中用自主无人驾驶飞行器（UAV）展示了我们方法的能力。
引用
@article{arxiv.1605.01923,
title = {UAV-based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction},
author = {Christian Mostegel and Markus Rumpler and Friedrich Fraundorfer and Horst Bischof},
journal= {arXiv preprint arXiv:1605.01923},
year = {2016}
}
备注
This paper was accepted to the 7th International Workshop on Computer Vision in Vehicle Technology (CVVT 2016) and will appear in IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016. The copyright was transferred to IEEE (ieee.org). The paper will be available on IEEE Xplore(ieeexplore.ieee.org). This version of the paper also contains the supplementary material