论文标题
使用签名距离字段的公制单眼定位
Metric Monocular Localization Using Signed Distance Fields
论文作者
论文摘要
公制定位在基于视觉的导航中起着至关重要的作用。为了克服在外观变化下匹配光度法的降解，最近的研究诉诸引入了先前场景结构的几何约束。在本文中，我们使用签名的距离字段（SDF）作为全局地图表示，为单眼摄像机提供了一种公制定位方法。利用来自SDF的体积距离信息，我们旨在放宽以前方法中局部束调整（BA）准确结构的假设。通过将距离因子与时间视觉限制紧密耦合，我们的系统纠正了探视度漂移，并通过本地结构共同优化了全局相机姿势。我们验证室内和室外公共数据集的建议方法。与最先进的方法相比，它通过最小的传感器配置实现了可比的性能。
Metric localization plays a critical role in vision-based navigation. For overcoming the degradation of matching photometry under appearance changes, recent research resorted to introducing geometry constraints of the prior scene structure. In this paper, we present a metric localization method for the monocular camera, using the Signed Distance Field (SDF) as a global map representation. Leveraging the volumetric distance information from SDFs, we aim to relax the assumption of an accurate structure from the local Bundle Adjustment (BA) in previous methods. By tightly coupling the distance factor with temporal visual constraints, our system corrects the odometry drift and jointly optimizes global camera poses with the local structure. We validate the proposed approach on both indoor and outdoor public datasets. Compared to the state-of-the-art methods, it achieves a comparable performance with a minimal sensor configuration.
