This paper reviews vision-based localization methods in GPS-denied environments and classifies the mainstream methods into Relative Vision Localization (RVL) and Absolute Vision Localization (AVL). For RVL, we discuss the broad application of optical flow in feature extraction-based Visual Odometry (VO) solutions and introduce advanced optical flow estimation methods. For AVL, we review recent advances in Visual Simultaneous Localization and Mapping (VSLAM) techniques, from optimization-based methods to Extended Kalman Filter (EKF) based methods. We also introduce the application of offline map registration and lane vision detection schemes to achieve Absolute Visual Localization. This paper compares the performance and applications of mainstream methods for visual localization and provides suggestions for future studies.
翻译:本文审查了全球定位系统封闭环境中基于愿景的定位方法,并将主流方法分为相对愿景本地化和绝对愿景本地化。对于RVL,我们讨论了光流在基于地貌提取的视觉测量(VO)解决方案中的广泛应用,并采用了先进的光流估计方法。关于AVL,我们审查了视觉同步本地化和绘图(VSLAM)技术的最新进展,从基于优化的方法到基于扩展卡尔曼过滤器(EKF)的方法。我们还介绍了应用离线地图注册和航道视觉探测计划实现绝对视觉本地化。本文比较了主流本地化方法的绩效和应用,并为今后的研究提出了建议。