Semantically Enhanced 3D Building Model Reconstruction from Terrestrial Laser-Scanning Data

Qian, Ying; Helmholz, Petra; Belton, David

doi:10.1061/(asce)su.1943-5428.0000232

Cited by 8 publications

(3 citation statements)

References 26 publications

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“…In recent years, with the development of algorithm, software and hardware in computer science, more studies focused on automatic 3D building modeling and achieved a great success (Agarwal et al, 2011), which can reconstruct 3D models in most scenarios. For instance, automatic methods based on point cloud data from laser or LiDAR (Yu, Helmholz, & Belton, 2017) not only guarantee very high modeling precision, but also eliminate the defects of limited architectural styles. However, these automatic methods need the assistance of professional and expensive devices to ensure the size and quality of data to obtain impressive results.…”

Section: Introductionmentioning

confidence: 99%

An Interactive platform for low-cost 3D building modeling from VGI data using convolutional neural network

2021

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The applications of 3D building models are limited as producing them requires massive labor and time costs as well as expensive devices. In this paper, we aim to propose a novel and web-based interactive platform, VGI3D, to overcome these challenges. The platform is designed to reconstruct 3D building models by using free images from internet users or volunteered geographic information (VGI) platform, even though not all these images are of high quality. Our interactive platform can effectively obtain each 3D building model from images in 30 seconds, with the help of user interaction module and convolutional neural network (CNN). The user interaction module provides the boundary of building facades for 3D building modeling. And this CNN can detect facade elements even though multiple architectural styles and complex scenes are within the images. Moreover, user interaction module is designed as simple as possible to make it easier to use for both of expert and non-expert users. Meanwhile, we conducted a usability testing and collected feedback from participants to better optimize platform and user experience. In general, the usage of VGI data reduces labor and device costs, and CNN simplifies the process of elements extraction in 3D building modeling. Hence, our proposed platform offers a promising solution to the 3D modeling community.

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Section: Introductionmentioning

confidence: 99%

An Interactive platform for low-cost 3D building modeling from VGI data using convolutional neural network

2021

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“…This idea also inspired other researchers and was applied to the 3D modelling of indoor environments (Tran et al 2019). In addition, the great method presented by Yu et al (Yu et al 2017) not only ensured a very high modelling precision but also stamped out the weaknesses of restricted architectural styles. However, to obtain impressive results, the above approaches have to reply on quite expensive point cloud acquisition devices not suitable for mass markets, and modelling procedures are time-consuming and laborious as well.…”

Section: Introductionmentioning

confidence: 99%

VGI3D: an Interactive and Low-Cost Solution for 3D Building Modelling from Street-Level VGI Images

2021

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Applications in smart cities are inseparable from the usage of three-dimensional (3D) building models. However, the cost of generating and constructing 3D building models with semantic information is high both in time and in labour. To solve this problem, we developed a web-based interactive system, VGI3D, with the ambition of becoming a VGI platform to collect 3D building models with semantic information by using the power of crowdsourcing. VGI3D is a platform-independent software program that is composed of a spatially relational database (PostgreSQL/PostGIS) for the storage and management of spatially geometrical data and other software modules, allowing users to import, analyse, reconstruct, visualise, modify and export 3D building models according to the OBJ/CityGML standard. In this paper, we present the VGI3D in detail, focusing on relevant technical implementations, and report the results of limited usability testing aimed at optimising the system and user experience. After limited expert and non-expert participants’ testing, we proved the usefulness of VGI3D and its promising value for the 3D modelling community.

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“…One is to apply the grammar-based automatic reconstruction method to generate a test model (Yu et al, 2015). The other way is to manually build the 3D model with commercial software tools, e.g.…”

Section: System Overviewmentioning

confidence: 99%

Evaluation of Model Recognition for Grammar-Based Automatic 3d Building Model Reconstruction

Qian¹,

Helmholz²,

Belton³

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In recent years, 3D city models are in high demand by many public and private organisations, and the steadily growing capacity in both quality and quantity are increasing demand. The quality evaluation of these 3D models is a relevant issue both from the scientific and practical points of view. In this paper, we present a method for the quality evaluation of 3D building models which are reconstructed automatically from terrestrial laser scanning (TLS) data based on an attributed building grammar. The entire evaluation process has been performed in all the three dimensions in terms of completeness and correctness of the reconstruction. Six quality measures are introduced to apply on four datasets of reconstructed building models in order to describe the quality of the automatic reconstruction, and also are assessed on their validity from the evaluation point of view.

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Semantically Enhanced 3D Building Model Reconstruction from Terrestrial Laser-Scanning Data

Cited by 8 publications

References 26 publications

An Interactive platform for low-cost 3D building modeling from VGI data using convolutional neural network

An Interactive platform for low-cost 3D building modeling from VGI data using convolutional neural network

VGI3D: an Interactive and Low-Cost Solution for 3D Building Modelling from Street-Level VGI Images

Evaluation of Model Recognition for Grammar-Based Automatic 3d Building Model Reconstruction

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