2019/12/09 by Yu Chen, Chen, Yu, Yisong Chen +3
Computer Science · Engineering · #Advanced Vision and Imaging #Computational Geometry and Mesh Generation #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Robotics and Sensor-Based Localization #cs.CV
paper · pdf · doi:10.48550/arxiv.1912.03858
9 pages, 9 figures
arxiv created 2019/12/09 · openalex publication_date 2019/12/09 · arxiv updated 2019/12/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
3D reconstruction has been developing all these two decades, from moderate to medium size and to large scale. It's well known that bundle adjustment plays an important role in 3D reconstruction, mainly in Structure from Motion(SfM) and Simultaneously Localization and Mapping(SLAM). While bundle adjustment optimizes camera parameters and 3D points as a non-negligible final step, it suffers from memory and efficiency requirements in very large scale reconstruction. In this paper, we study the development of bundle adjustment elaborately in both conventional and distributed approaches. The detailed derivation and pseudo code are also given in this paper.