3D reconstruction plays an increasingly important role in modern photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities. Even with low-altitude UAVs (Unmanned Aerial Vehicles), 3D reconstruction in complicated situations, such as urban canyons and indoor scenes, is challenging due to frequent tracking failures between camera frames and high data collection costs. Recently, spherical images have been extensively used due to the capability of recording surrounding environments from one camera exposure. In contrast to perspective images with limited FOV (Field of View), spherical images can cover the whole scene with full horizontal and vertical FOV and facilitate camera tracking and data acquisition in these complex scenes. With the rapid evolution and extensive use of professional and consumer-grade spherical cameras, spherical images show great potential for the 3D modeling of urban and indoor scenes. Classical 3D reconstruction pipelines, however, cannot be directly used for spherical images. Besides, there exist few software packages that are designed for the 3D reconstruction of spherical images. As a result, this research provides a thorough survey of the state-of-the-art for 3D reconstruction of spherical images in terms of data acquisition, feature detection and matching, image orientation, and dense matching as well as presenting promising applications and discussing potential prospects. We anticipate that this study offers insightful clues to direct future research.

翻译：三维重建在现代摄影测量系统中发挥着日益重要的作用。传统的卫星或航空遥感平台可为大规模地形和城市的三维重建提供必要的数据源。即使采用低空无人机，在城市峡谷和室内场景等复杂环境下的三维重建仍面临挑战，主要源于相机帧间频繁的跟踪失败以及高昂的数据采集成本。近年来，球面图像因能在单次相机曝光中记录周围环境而被广泛应用。与视场角有限的透视图像不同，球面图像可覆盖完整水平与垂直视场的全场景，有助于在复杂场景中实现相机跟踪与数据采集。随着专业级和消费级球面相机的快速发展与广泛使用，球面图像在城市和室内场景的三维建模中展现出巨大潜力。然而，传统三维重建流程无法直接用于球面图像，且目前专门针对球面图像三维重建的软件包极少。为此，本文从数据采集、特征检测与匹配、影像定向以及密集匹配等方面，对球面图像三维重建的最新进展进行了全面综述，同时展示了应用前景并讨论了潜在发展方向。我们期望本研究能为未来研究提供富有洞察力的指引。