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.

摘要

虚拟现实（VR）场景中洪水灾害的可视化有助于灾害知识的表示和共享，可以有效提高用户对灾害信息的认知效率。然而，现有的虚拟现实洪水灾害场景可视化方法存在渲染效率低、用户体验差等不足。本文提出了一种基于高斯模糊的VR洪水场景隧道视觉优化方法。研究了关键技术，如考虑人类视觉系统特性的感兴趣区域（ROI）计算和隧道视觉优化。原型系统已被开发并用于进行实验案例分析。