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Structure-from-motion using lines: Representation, triangulation, and bundle adjustment

机译:使用线的运动结构:表示,三角剖分和束调整

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We address the problem of camera motion and 3D 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 Micker coordinates to represent the 3D lines, we propose a maximum likelihood algorithm, relying on linearizing the Plucker constraint and on a Plucker correction procedure, computing the closest Plucker coordinates to a given 6-vector. Second, we consider the bundle adjustment problem, which is essentially a nonlinear optimization process on camera motion and 3D line parameters. 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 four parameters with an unconstrained optimization engine. We compare Our algorithms to existing ones on simulated and real data. Results show that our triangulation algorithm outperforms standard linear and bias-corrected quasi-linear algorithms, and that bundle adjustment using our orthonormal representation yields results similar to the standard maximum likelihood trifocal tensor algorithm, while being usable for any number of views. (c) 2005 Elsevier Inc. All rights reserved.
机译:我们从多个视图(从初始化到最终束调整)的线对应关系解决了摄像机运动和3D结构重建的问题。处理线要素时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,基于表示3D线的Micker坐标,我们提出了一种最大似然算法,该算法依靠线性化Plucker约束和Plucker校正程序,计算最接近给定6矢量的Plucker坐标。其次,我们考虑束调整问题,这实际上是对摄像机运动和3D线参数的非线性优化过程。先前3D线的过度参数化会引起量规自由度和/或内部一致性约束。我们提出了正交表示法,它允许使用无约束的优化引擎使用最少的四个参数方便地对3D线进行非线性优化。我们将我们的算法与基于模拟和真实数据的现有算法进行比较。结果表明,我们的三角剖分算法优于标准的线性算法和经偏差校正的准线性算法,并且使用我们的正交表示的束调整产生的结果类似于标准最大似然三焦点张量算法,同时可用于任意数量的视图。 (c)2005 Elsevier Inc.保留所有权利。

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