Bundle Adjustment Revisited
This is an incremental review for researchers in computer vision and robotics working on SfM and SLAM.
The paper tackles the memory and efficiency challenges of bundle adjustment in large-scale 3D reconstruction, reviewing both conventional and distributed approaches with detailed derivations and pseudo code.
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.