航空图像的视觉地点识别：一项调查

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems Pub Date : 2024-10-23 DOI:10.1016/j.robot.2024.104837

Ivan Moskalenko , Anastasiia Kornilova , Gonzalo Ferrer

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引用次数: 0

摘要

航空图像及其在视觉定位中的直接应用是许多机器人和计算机视觉任务的基本问题。虽然全球导航卫星系统（GNSS）是解决空中定位问题的标准默认解决方案，但它受到许多限制，例如信号不稳定或解决方案不可靠，使得这一方案不那么理想。因此，视觉地理定位正在成为一种可行的替代方案。然而，将视觉地点识别（VPR）任务应用于航空图像面临着巨大的挑战，包括天气变化和重复模式。目前的视觉地点识别（VPR）评测在很大程度上忽视了航空数据的特定环境。本文介绍了一种专门针对航空图像领域的 VPR 技术进行评估的方法，对各种方法及其性能进行了全面评估。不过，我们不仅比较了各种 VPR 方法，还证明了在构建地图瓦片时选择适当缩放和重叠级别的重要性，以便在航空图像中实现 VPR 算法的最高效率。代码可从我们的 GitHub 代码库中获取 - https://github.com/prime-slam/aero-vloc。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Visual place recognition for aerial imagery: A survey

Aerial imagery and its direct application to visual localization is an essential problem for many Robotics and Computer Vision tasks. While Global Navigation Satellite Systems (GNSS) are the standard default solution for solving the aerial localization problem, it is subject to a number of limitations, such as, signal instability or solution unreliability that make this option not so desirable. Consequently, visual geolocalization is emerging as a viable alternative. However, adapting Visual Place Recognition (VPR) task to aerial imagery presents significant challenges, including weather variations and repetitive patterns. Current VPR reviews largely neglect the specific context of aerial data. This paper introduces a methodology tailored for evaluating VPR techniques specifically in the domain of aerial imagery, providing a comprehensive assessment of various methods and their performance. However, we not only compare various VPR methods, but also demonstrate the importance of selecting appropriate zoom and overlap levels when constructing map tiles to achieve maximum efficiency of VPR algorithms in the case of aerial imagery. The code is available on our GitHub repository — https://github.com/prime-slam/aero-vloc.

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来源期刊

Robotics and Autonomous Systems 工程技术-机器人学

CiteScore

9.00

自引率

7.00%

发文量

164

审稿时长

4.5 months

期刊介绍： Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.