多视图结构和运动从线对应

A. Bartoli, P. Sturm
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引用次数: 36

摘要

我们解决了相机运动和结构重建的问题,从多个视图的线对应,从初始化到最终的束调整。处理线特征的主要困难之一是它们的代数表示。首先,我们考虑三角剖分问题。基于Plucker坐标来表示线条,我们提出了一种最大似然算法,该算法依赖于对Plucker约束进行线性化,并基于一个Plucker校正程序来计算最接近给定6向量的Plucker坐标。其次,我们考虑了束平差问题。以前的3D线的过度参数化会导致测量自由和/或内部一致性约束。我们提出了标准正交表示,它允许在无约束非线性优化器中使用最小4个参数对3D线进行方便的非线性优化。我们在模拟和真实数据上将我们的算法与现有算法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple-view structure and motion from line correspondences
We address the problem of camera motion and structure reconstruction from line correspondences across multiple views, from initialization to final bundle adjustment. One of the main difficulties when dealing with line features is their algebraic representation. First, we consider the triangulation problem. Based on Plucker coordinates to represent the lines, we propose a maximum likelihood algorithm, relying on linearising the Plucker constraint, and on a Plucker correction procedure to compute the closest Plucker coordinates to a given 6-vector. Second, we consider the bundle adjustment problem. Previous overparameterizations of 3D lines induce gauge freedoms and/or internal consistency constraints. We propose the orthonormal representation, which allows handy nonlinear optimization of 3D lines using the minimum 4 parameters, within an unconstrained nonlinear optimizer. We compare our algorithms to existing ones on simulated and real data.
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