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State‐of‐the‐art in Automatic 3D Reconstruction of Structured Indoor Environments
Computer Graphics Forum ( IF 2.5 ) Pub Date : 2020-05-01 , DOI: 10.1111/cgf.14021
Giovanni Pintore 1 , Claudio Mura 2 , Fabio Ganovelli 3 , Lizeth Fuentes‐Perez 2 , Renato Pajarola 2 , Enrico Gobbetti 1
Affiliation  

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 survey, 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.

中文翻译:

结构化室内环境自动 3D 重建的最新技术

从捕获的数据中创建真实世界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应用。鉴于室内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,但许多开放的研究问题仍然存在。在本次调查中,我们提供了该领域的最新综合观点,桥接了来自计算机图形学和计算机视觉的互补观点。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成部分,并查看它们是如何结合到在建筑层面工作的可扩展解决方案中的。最后指出相关研究问题并分析研究趋势。
更新日期:2020-05-01
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