碎片工件自动装配中的全局一致性

Antonio García Castañeda, Benedict J. Brown, S. Rusinkiewicz, T. Funkhouser, T. Weyrich
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引用次数: 29

摘要

碎片物体的自动重建在考古学中引起了极大的兴趣,在考古学中,人工制品经常处于断裂状态。在本文中,我们主要研究从先前确定的成对匹配中自动聚集碎片簇的问题。任何自动化聚类聚集技术都面临着错误积累的挑战,这使得随着聚类的增长,从真实匹配中辨别错误变得越来越困难。因此,许多装配算法引入了一个全局松弛阶段,以均匀地分布整个集群的对齐误差,最大限度地减少主要的不一致。然而,误差累积限制了自动化装配系统在实践中可以处理的问题规模。在本文中,我们展示了对传统松弛方案的两种谨慎修改如何有助于大大提高这一限制。与以前的工作相比,我们在装配过程的搜索阶段更早地集成了全局松弛。此外,我们不固定组装片段之间的连接,而是在整个组装过程中保持它们的灵活性。通过修改两个代表性的装配算法,我们证明了该方法的有效性。使用一个具有挑战性的壁画数据集的例子,我们表明这些修改比传统策略实现了更大的重建规模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global Consistency in the Automatic Assembly of Fragmented Artefacts
Automatic reconstruction of fragmented objects is of great interest in archaeology, where artefacts are often found in a fractured state. In this paper, we focus on the problem of automatically agglomerating clusters of fragments from previously determined pairwise matches. Common to any automated cluster agglomeration technique is the challenge of error accumulation, making it increasingly difficult to discern false from true matches as the assembly grows. Many assembly algorithms therefore introduce a global relaxation phase to distribute alignment errors evenly across the cluster, minimising major inconsistencies. Nevertheless, error accumulation limits the problem size automated assembly systems can handle in practice. In this paper we show how two careful modifications of the traditional relaxation scheme help lift this limit considerably. In contrast to previous work, we integrate global relaxation earlier, in the search phase of the assembly process. In addition, we do not fix connections between assembled fragments, but rather leave them flexible throughout the assembly. By modifying two representative assembly algorithms, we demonstrate the effectiveness of our approach. Using the example of a challenging fresco dataset, we show that these modifications achieve larger reconstruction sizes than traditional strategies.
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