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.
翻译:3D重建从中度到中度和大规模发展了整整二十年,从中度到中度到大度。众所周知,捆绑式调整在3D重建中发挥着重要作用,主要是在运动结构以及同时本地化和绘图(SLAM)中。捆绑式调整优化了摄像参数和3D点,作为不可忽略的最后一步,但在大规模重建中却受到记忆和效率要求的影响。在本文中,我们仔细研究了常规和分布式方法的捆绑式调整发展。本文还介绍了详细的衍生法和假代码。