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3D reconstruction plays an increasingly important role in modernphotogrammetric systems. Conventional satellite or aerial-based remote sensing(RS) platforms can provide the necessary data sources for the 3D reconstructionof large-scale landforms and cities. Even with low-altitude UAVs (UnmannedAerial Vehicles), 3D reconstruction in complicated situations, such as urbancanyons and indoor scenes, is challenging due to the frequent tracking failuresbetween camera frames and high data collection costs. Recently, sphericalimages have been extensively exploited due to the capability of recordingsurrounding environments from one camera exposure. Classical 3D reconstructionpipelines, however, cannot be used for spherical images. Besides, there existfew software packages for 3D reconstruction of spherical images. Based on theimaging geometry of spherical cameras, this study investigates the algorithmsfor the relative orientation using spherical correspondences, absoluteorientation using 3D correspondences between scene and spherical points, andthe cost functions for BA (bundle adjustment) optimization. In addition, anincremental SfM (Structure from Motion) workflow has been proposed forspherical images using the above-mentioned algorithms. The proposed solution isfinally verified by using three spherical datasets captured by bothconsumer-grade and professional spherical cameras. The results demonstrate thatthe proposed SfM workflow can achieve the successful 3D reconstruction ofcomplex scenes and provide useful clues for the implementation in open-sourcesoftware packages. The source code of the designed SfM workflow would be madepublicly available.

3D Reconstruction of Spherical Images based on Incremental Structure from Motion