A review of computer graphics approaches to urban modeling from a machine learning perspective

Urban modeling facilitates the generation of virtual environments for various scenarios about cities. It requires expertise and consideration, and therefore consumes massive time and computation resources. Nevertheless, related tasks sometimes result in dissatisfaction or even failure. These challen...

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Bibliographic Details
Published in:Frontiers of information technology & electronic engineering 2021-07, Vol.22 (7), p.915-925
Main Authors: Feng, Tian, Fan, Feiyi, Bednarz, Tomasz
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Cities
Communications Engineering
Computer graphics
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Computers
Deep learning
Electrical Engineering
Electronics and Microelectronics
Information technology
Instrumentation
Machine learning
Modelling
Networks
Neural networks
Review
Urban areas
Virtual environments
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Summary:Urban modeling facilitates the generation of virtual environments for various scenarios about cities. It requires expertise and consideration, and therefore consumes massive time and computation resources. Nevertheless, related tasks sometimes result in dissatisfaction or even failure. These challenges have received significant attention from researchers in the area of computer graphics. Meanwhile, the burgeoning development of artificial intelligence motivates people to exploit machine learning, and hence improves the conventional solutions. In this paper, we present a review of approaches to urban modeling in computer graphics using machine learning in the literature published between 2010 and 2019. This serves as an overview of the current state of research on urban modeling from a machine learning perspective.
ISSN:2095-9184
2095-9230
DOI:10.1631/FITEE.2000141