论文标题
你能相信你的姿势吗？视觉定位中的置信度估计
Can You Trust Your Pose? Confidence Estimation in Visual Localization
论文作者
论文摘要
大规模环境中的摄像头姿势估计仍然是一个空旷的问题，尽管最近有令人鼓舞的结果，但在某些情况下仍可能失败。迄今为止，这项研究集中在改善估计管道的子组件上，以实现更准确的姿势。但是，即使姿势估计的正确性在几种视觉本地化应用程序（例如在自主导航中）至关重要，因此无法保证结果是正确的。在本文中，我们引起了一个新的研究问题，即构成置信度估计，我们旨在量化视觉估计的姿势的可靠性。我们开发了一种新颖的置信度措施来完成这项任务，并表明它可以灵活地应用于不同的数据集，室内或室外，以及用于各种视觉定位管道。我们还表明，所提出的技术可用于实现次要目标：提高现有姿势估计管道的准确性。最后，所提出的方法是计算重量重量，并且仅增加了姿势估计的计算工作的可忽略不计。
Camera pose estimation in large-scale environments is still an open question and, despite recent promising results, it may still fail in some situations. The research so far has focused on improving subcomponents of estimation pipelines, to achieve more accurate poses. However, there is no guarantee for the result to be correct, even though the correctness of pose estimation is critically important in several visual localization applications,such as in autonomous navigation. In this paper we bring to attention a novel research question, pose confidence estimation,where we aim at quantifying how reliable the visually estimated pose is. We develop a novel confidence measure to fulfil this task and show that it can be flexibly applied to different datasets,indoor or outdoor, and for various visual localization pipelines.We also show that the proposed techniques can be used to accomplish a secondary goal: improving the accuracy of existing pose estimation pipelines. Finally, the proposed approach is computationally light-weight and adds only a negligible increase to the computational effort of pose estimation.
