SBA: A Software Package for Generic Sparse Bundle Adjustment
SBA: A Software Package for Generic Sparse Bundle Adjustment
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DOI：
10.1145/1486525.1486527
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发表时间：
2009-03-01
影响因子：
2.7
通讯作者：
Argyros, Antonis A.
中科院分区：
文献类型：
--
作者：
Lourakis, Manolis I. A.;Argyros, Antonis A.
束平差构成了一个大型的非线性最小二乘问题，通常作为基于特征的结构和运动估计计算机视觉算法的最后一步来解决，以获得最佳估计。由于所涉及的参数非常大，当应用于光束法平差时，通用最小二乘算法会产生高的计算和存储成本。幸运的是，某些参数子组之间缺乏相互作用导致相应的雅可比矩阵稀疏，这一事实可以用来实现相当大的计算节省。本文介绍了sba，一个公开可用的C/C++软件包，用于实现通用光束法平差，具有高效率和灵活的参数化。
Bundle adjustment constitutes a large, nonlinear least-squares problem that is often solved as the last step of feature-based structure and motion estimation computer vision algorithms to obtain optimal estimates. Due to the very large number of parameters involved, a general purpose least-squares algorithm incurs high computational and memory storage costs when applied to bundle adjustment. Fortunately, the lack of interaction among certain subgroups of parameters results in the corresponding Jacobian being sparse, a fact that can be exploited to achieve considerable computational savings. This article presents sba, a publicly available C/C++ software package for realizing generic bundle adjustment with high efficiency and flexibility regarding parameterization.