Synthetic images generation for semantic understanding in facility management

IF 3.1 Q2 CONSTRUCTION & BUILDING TECHNOLOGY
Luca Rampini, F. Re Cecconi
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引用次数: 1

Abstract

Purpose This study aims to introduce a new methodology for generating synthetic images for facility management purposes. The method starts by leveraging the existing 3D open-source BIM models and using them inside a graphic engine to produce a photorealistic representation of indoor spaces enriched with facility-related objects. The virtual environment creates several images by changing lighting conditions, camera poses or material. Moreover, the created images are labeled and ready to be trained in the model. Design/methodology/approach This paper focuses on the challenges characterizing object detection models to enrich digital twins with facility management-related information. The automatic detection of small objects, such as sockets, power plugs, etc., requires big, labeled data sets that are costly and time-consuming to create. This study proposes a solution based on existing 3D BIM models to produce quick and automatically labeled synthetic images. Findings The paper presents a conceptual model for creating synthetic images to increase the performance in training object detection models for facility management. The results show that virtually generated images, rather than an alternative to real images, are a powerful tool for integrating existing data sets. In other words, while a base of real images is still needed, introducing synthetic images helps augment the model’s performance and robustness in covering different types of objects. Originality/value This study introduced the first pipeline for creating synthetic images for facility management. Moreover, this paper validates this pipeline by proposing a case study where the performance of object detection models trained on real data or a combination of real and synthetic images are compared.
面向设施管理语义理解的合成图像生成
目的本研究旨在介绍一种为设施管理目的生成合成图像的新方法。该方法首先利用现有的3D开源BIM模型,并在图形引擎中使用它们来生成富含设施相关对象的室内空间的真实感表示。虚拟环境通过更改照明条件、相机姿势或材质来创建多个图像。此外,创建的图像被标记并准备在模型中进行训练。设计/方法论/方法本文侧重于描述对象检测模型的挑战,以利用设施管理相关信息丰富数字双胞胎。插座、电源插头等小物体的自动检测需要大的、有标签的数据集,创建这些数据集既昂贵又耗时。本研究提出了一种基于现有三维BIM模型的解决方案,以生成快速、自动标记的合成图像。发现本文提出了一个创建合成图像的概念模型,以提高训练设施管理对象检测模型的性能。结果表明,虚拟生成的图像是集成现有数据集的强大工具,而不是真实图像的替代品。换句话说,虽然仍然需要真实图像的基础,但引入合成图像有助于增强模型在覆盖不同类型对象方面的性能和稳健性。独创性/价值这项研究引入了第一个为设施管理创建合成图像的管道。此外,本文通过提出一个案例研究来验证这一管道,其中比较了在真实数据或真实图像和合成图像的组合上训练的目标检测模型的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Construction Innovation-England
Construction Innovation-England CONSTRUCTION & BUILDING TECHNOLOGY-
CiteScore
7.10
自引率
12.10%
发文量
71
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