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Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration

机译:Go-ICP:3D ICP点集套准的全球最佳解决方案

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摘要

The Iterative Closest Point (ICP) algorithm is one of the most widely used methods for point-set registration. However, being based on local iterative optimization, ICP is known to be susceptible to local minima. Its performance critically relies on the quality of the initialization and only local optimality is guaranteed. This paper presents the first globally optimal algorithm, named Go-ICP, for Euclidean (rigid) registration of two 3D point-sets under the L2 error metric defined in ICP. The Go-ICP method is based on a branch-and-bound scheme that searches the entire 3D motion space SE(3) . By exploiting the special structure of SE(3) geometry, we derive novel upper and lower bounds for the registration error function. Local ICP is integrated into the BnB scheme, which speeds up the new method while guaranteeing global optimality. We also discuss extensions, addressing the issue of outlier robustness. The evaluation demonstrates that the proposed method is able to produce reliable registration results regardless of the initialization. Go-ICP can be applied in scenarios where an optimal solution is desirable or where a good initialization is not always available.
机译:迭代最近点(ICP)算法是用于点集注册的最广泛使用的方法之一。但是,基于局部迭代优化,ICP容易受到局部最小值的影响。它的性能主要取决于初始化的质量,并且只能保证局部最优。本文提出了第一个全局最优算法Go-ICP,用于在ICP中定义的L2误差指标下对两个3D点集进行欧几里得(刚性)配准。 Go-ICP方法基于搜索整个3D运动空间SE(3)的分支定界方案。通过利用SE(3)几何结构的特殊结构,我们得出配准误差函数的新颖上限和下限。本地ICP已集成到BnB方案中,从而在保证全局最优性的同时加快了新方法的速度。我们还将讨论扩展,以解决离群值鲁棒性的问题。评估表明,所提出的方法无论初始化如何都能产生可靠的注册结果。 Go-ICP可以应用在需要最佳解决方案或始终没有良好初始化的场景中。

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