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Efficient and intuitive representation of floods can improve people's perception, which is useful for flood emergency management and decision making. However, the current methods of visualizing flood disaster scenes have the shortcomings of data redundancy and low-efficiency. The interference of the complex background can be avoided through region of interest (ROI) extraction, because the attention will be quickly attracted by a few salient visual objects. First, the characteristics of the flood disaster scene object are analysed, and the method for scene division and data organization is established. Second, the region of interest is extracted according to the time series data of the flood evolution process simulated using cellular automata, and the dynamic identification model of the objects of interest is established. Then, a dynamic scheduling queue model with service interruption is designed to optimize the rendering efficiency of flood scenes and improve the perception efficiency. Finally, a prototype visualization system was developed and the experimental results show that approximately 30% of the redundant data are reduced, and the scene rendering efficiency is increased by approximately 15%. The non-ROI visualization is weakened by using the rules of human visual cognition, which improves the perception efficiency of flood scenes. [ABSTRACT FROM AUTHOR]

Holographic projection technology can provide a more intuitive and efficient visualization effect for a digital twin bridge construction scene. However, pre-rendering methods in the existing research work are usually used to implement holographic visualization, which is static display. The above-mentioned methods for static display have many shortcomings, such as poor adaptability, low rendering efficiency and lack of real-time. A dynamic holographic modelling approach is proposed for the augmented visualization of digital twin scenes for bridge construction. Firstly, a dynamic segmentation algorithm with adaptive screen size was designed to high-efficiently generate holographic scenes. Secondly, a motion blur control method was designed to improve the rendering efficiency of holographic scenes according to human visual characteristics. Finally, a prototype system was developed, and the corresponding experimental analysis was completed. The experimental results show that the method proposed in this article can support adaptive screen size image segmentation and real-time generation of holographic scenes for bridge construction. The amount of scene data can be reduced to more than 30%, which significantly improves rendering efficiency and reduces glare. [ABSTRACT FROM AUTHOR]

Crowd evacuation simulation using virtual reality (VR) is significant for digital emergency response construction. However, existing evacuation simulation studies suffer from poor adaptation to complex environments, inefficient evacuations, and poor simulation effects and do not fully consider the impacts of specific disaster environments on crowd evacuation. To more realistically express the crowd evacuation results obtained under the influence of fire environments and the subjective consciousness of pedestrians in subway stations, we designed a dynamic pedestrian evacuation path planning method under multiple constraints, analysed the influences of an 'environmental role' and a 'subjective initiative' on crowd evacuation, established an improved social force model (ISFM)-based crowd evacuation simulation method in VR, developed a prototype system and conducted experimental analyses. The experimental results show that the crowd evacuation time of the ISFM is affected by the disaster severity. In simulation experiments without disaster scenarios, the improved model's crowd evacuation efficiency improved by averages of 12.53% and 15.37% over the commercial Pathfinder software and the original social force model, respectively. The method described herein can effectively support real-time VR crowd evacuation simulation under multiexit and multifloor conditions and can provide technical support for emergency evacuation learning and management decision analyses involving subway fires. [ABSTRACT FROM AUTHOR]

Virtual construction has become an important approach to the high-quality development of high-speed railways, but existing methods have problems such as low efficiency in generating virtual construction scenes and the inability to reuse construction knowledge. To support the rapid visual representation of multiple types of construction processes and construction methods, a template-based knowledge reuse method is proposed. The method includes using a component-based modeling mode to build body structure models of a high-speed railway project and generate a 3D scene; decomposing the construction process and building a construction process knowledge base; establishing joint linkage models of construction machinery and forming a construction method knowledge template; and fusing multiple types of information according to a time sequence to visualize the construction process. Based on the template-based knowledge reuse method, a prototype system was developed, and virtual construction experiments were carried out. The results show that this method achieves the reuse of construction knowledge at different levels including construction machinery level, construction method level, and work site level. Compared with animation software for virtual construction, this method improves the production efficiency by 87%. Moreover, this method can provide a multilevel knowledge reuse scheme for diversified virtual construction. [ABSTRACT FROM AUTHOR]

The objective of disaster scenes is to share location-based risk information to a large audience in an effective and intuitive way. However, current studies on three-dimensional (3D) representation for dam-break floods have the following limitations: (1) they are lacking a reasonable logic to organize the whole process of dam-break floods, (2) they present information in a way that cannot be easily understood by laypersons. Geospatial storytelling helps to create exciting experiences and to explain complex relationships of geospatial phenomena. This article proposes a three-dimensional virtual representation method for the whole process of dam-break floods from a geospatial storytelling perspective. The creation of a storyline and a storytelling-oriented representation of dam-break floods are discussed in detail. Finally, a prototype system based on WebGL is developed to conduct an experiment analysis. The results of the experiment show that the proposed method can effectively support 3D representation of the spatiotemporal process of dam-break floods. Furthermore, the statistical results indicate that the storytelling is useful for assisting participants in understanding the occurrence and development of dam-break floods, and is applicable to the popularization of disaster science for the general public. [ABSTRACT FROM AUTHOR]

As an important technology of digital construction, real 3D models can improve the immersion and realism of virtual reality (VR) scenes. The large amount of data for real 3D scenes requires more effective rendering methods, but the current rendering optimization methods have some defects and cannot render real 3D scenes in virtual reality. In this study, the location of the viewing frustum is predicted by a Kalman filter, and eye-tracking equipment is used to recognize the region of interest (ROI) in the scene. Finally, the real 3D model of interest in the predicted frustum is rendered first. The experimental results show that the method of this study can predict the frustrum location approximately 200 ms in advance, the prediction accuracy is approximately 87%, the scene rendering efficiency is improved by 8.3%, and the motion sickness is reduced by approximately 54.5%. These studies help promote the use of real 3D models in virtual reality and ROI recognition methods. In future work, we will further improve the prediction accuracy of viewing frustums in virtual reality and the application of eye tracking in virtual geographic scenes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]