An Interactive platform for low-cost 3D building modeling from VGI data using convolutional neural network. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Fan, Hongchao; Kong, Gefei; Zhang, Chaoquan
• Is Part Of: Big earth data. Volume 5:Issue 1(2021)
• Page Start: 49
• Page End: 65
• Publication Date: 2021-01-02
• Subjects: 3D building modeling -- VGI -- convolutional neural network -- user interaction -- low cost; Earth sciences -- Periodicals; Earth sciences -- Research -- Periodicals; Geographic information systems Periodicals; 550
• DOI: 10.1080/20964471.2021.1886391
• Languages: English
• ISSNs: 2096-4471

Abstract

ABSTRACT: 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.