阮舜毅, 康俊锋. 移动增强现实可视化下灾害场景加载的优化方法[J]. 武汉大学学报 ( 信息科学版), 2020, 45(9): 1422-1428. DOI: 10.13203/j.whugis20190477
引用本文: 阮舜毅, 康俊锋. 移动增强现实可视化下灾害场景加载的优化方法[J]. 武汉大学学报 ( 信息科学版), 2020, 45(9): 1422-1428. DOI: 10.13203/j.whugis20190477
RUAN Shunyi, KANG Junfeng. Optimization Method of Disaster Scene Loading Under Mobile Augmented Reality Visualization[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1422-1428. DOI: 10.13203/j.whugis20190477
Citation: RUAN Shunyi, KANG Junfeng. Optimization Method of Disaster Scene Loading Under Mobile Augmented Reality Visualization[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1422-1428. DOI: 10.13203/j.whugis20190477

移动增强现实可视化下灾害场景加载的优化方法

Optimization Method of Disaster Scene Loading Under Mobile Augmented Reality Visualization

  • 摘要: 地理信息可视化分析是灾害研究的重要手段,而移动增强现实(mobile augmented reality,MAR)为可视化注入了新的活力。灾害MAR可视化通常会涉及到多源数据的处理,这对移动设备的性能提出了挑战。为实现灾害移动增强可视化场景的流畅稳定加载,提出了一种基于流的场景加载优化方法。该方法利用多细节层次模型(level of detail,LOD)构建基础场景,拆分压缩后存储于服务器。客户端按照需要向服务器请求数据,然后依据传输策略控制数据的调度,并采用缓存机制缓解加载时的计算压力。同时搭建了一个原型系统用于测试方法的性能。实验结果表明,提出的优化方法可以实现灾害MAR可视化场景的快速加载,突破了Microsoft HoloLens设备的数据量限制,并在不同数据量的情况下表现稳定。

     

    Abstract: Geographic information system(GIS) visualization analysis is an important method for disaster research, and mobile augmented reality (MAR) brings new vitality into GIS visualization.MAR visualization of disaster scenes usually needs to process multi-source and massive data, which challenges the performance of MAR device. To achieve smooth and stable loading capability for MAR visualization of disaster scenes, we proposed a flow-based optimization method for disaster scene loading. First, a MAR scene was split and compressed by the level of detail(LOD) method, then the scene data were stored on a data server. When a MAR client browsed data in a determined area, our optimized method can help to request the data from the server, and control the data loading by using our designed transmission strategy and alleviate the bandwidth pressure through our designed caching mechanism. A prototype system was built to test the performance of the optimized method. Experimental results show that the optimized method can achieve fast loading performance for MAR visualization of disaster scenes, and breakthrough the data volume limit on HoloLens device, and succeed stably under different data volume.

     

/

返回文章
返回