结构化室内环境的自动三维重建

G. Pintore, Claudio Mura, F. Ganovelli, Lizeth Joseline Fuentes Perez, R. Pajarola, Enrico Gobbetti
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引用次数: 5

摘要

从捕获的数据中创建真实室内场景的高级结构化3D模型是一项基本任务,在许多领域都有重要的应用。考虑到内部环境的复杂性和可变性,以及处理嘈杂和部分捕获数据的需要,尽管在过去十年中取得了实质性进展,但仍存在许多开放的研究问题。在本教程中,我们提供了该领域最新的综合视图,连接了来自计算机图形学和计算机视觉的互补视图。在提供输入源的特征之后,我们定义了输出模型的结构和用于弥合不完美源和期望输出之间差距的先验。然后,我们确定并讨论结构化重建管道的主要组件,并审查它们如何在建筑级别工作的可扩展解决方案中组合。最后指出了相关的研究问题,并分析了研究趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic 3D reconstruction of structured indoor environments
Creating high-level structured 3D models of real-world indoor scenes from captured data is a fundamental task which has important applications in many fields. Given the complexity and variability of interior environments and the need to cope with noisy and partial captured data, many open research problems remain, despite the substantial progress made in the past decade. In this tutorial, we provide an up-to-date integrative view of the field, bridging complementary views coming from computer graphics and computer vision. After providing a characterization of input sources, we define the structure of output models and the priors exploited to bridge the gap between imperfect sources and desired output. We then identify and discuss the main components of a structured reconstruction pipeline, and review how they are combined in scalable solutions working at the building level. We finally point out relevant research issues and analyze research trends.
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