Paper Info
Title
Tunnel Vision Optimization Method For Vr Flood Scenes Based On Gaussian Blur
Abstract
The visualization of flood disasters in virtual reality (VR) scenes is useful for the representation and sharing of disaster knowledge and can effectively improve users' cognitive efficiency in comprehending disaster information. However, the existing VR methods of visualizing flood disaster scenes have some shortcomings, such as low rendering efficiency and poor user experience. In this paper, a tunnel vision optimization method for VR flood scenes based on Gaussian blur is proposed. The key techniques are studied, such as region of interest (ROI) calculation and tunnel vision optimization considering the characteristics of the human visual system. A prototype system has been developed and used to carry out an experimental case analysis. The experimental results show that the number of triangles drawn in a flood VR scene is reduced by approximately 30%-40% using this method and that the average frame rate is stable at approximately 90 frames per second (fps), significantly improving the efficiency of scene rendering and reducing motion sickness.
Year
DOI
Venue
2021
10.1080/17538947.2021.1886359
INTERNATIONAL JOURNAL OF DIGITAL EARTH
Keywords
DocType
Volume
Flood disaster, virtual reality, Gaussian blur, tunnel vision, scene optimization
Journal
14
Issue
ISSN
Citations 
7
1753-8947
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
Lin Fu103.72
Jun Zhu200.34
Weilian Li355.52
Qing Zhu400.34
Bingli Xu500.68
Yakun Xie602.37
Yunhao Zhang785.26
Ya Hu800.68
Jingtao Lu900.34
Pei Dang1000.68
Jigang You1100.68