虚拟环境下基于VIO的运动恢复结构
VIO-Aided Structure from Motion Under Challenging Environments
摘要：
在本文中，我们提出了一个强大的和有效的运动恢复结构管道准确的三维重建在具有挑战性的环境下，利用相机的姿态信息从视觉惯性里程计。具体来说，我们提出了一种几何验证方法，通过考虑候选图像对的先验几何配置来过滤掉不匹配。此外，我们引入了一种高效的和可扩展的重建方法，依赖于批量图像配准和鲁棒的光束法平差，都利用可靠的局部测距估计。大量的实验结果表明，我们的管道表现优于国家的最先进的SfM方法在重建精度和鲁棒性方面具有挑战性的序列图像集合。
英文摘要：
In this paper, we present a robust and efficient Structure from Motion pipeline for accurate 3D reconstruction under challenging environments by leveraging the camera pose information from a visual-inertial odometry. Specifically, we propose a geometric verification method to filter out mismatches by considering the prior geometric configuration of candidate image pairs. Furthermore, we introduce an efficient and scalable reconstruction approach that relies on batched image registration and robust bundle adjustment, both leveraging the reliable local odometry estimation. Extensive experimental results show that our pipeline performs better than the state-of-the-art SfM approaches in terms of reconstruction accuracy and robustness for challenging sequential image collections.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
