网络环境下全景图和点云数据快速融合可视化方法

Visualization Method for Fast Fusion of Panorama and Point Cloud Data in Network Environment

现有多源数据融合可视化方法对数据精度要求高,匹配过程复杂,且传统点云的组织索引方式冗余,面对复杂数据的动态性较差,索引效率较低,难以支撑在网络环境下进行多源数据高效可视化交互.针对上述问题,提出面向网络轻量化应用的全景图与点云数据快速融合可视化方法.探讨了二维影像与三维点云的快速映射匹配机制、非规则性八叉树点云优化组织与多细节层次(levels of detail,LOD)动态调度等关键技术;并设计了融合场景跨模态交互分析机制,以实现全景图和点云数据快速融合可视化;最后构建了原型系统并进行案例实验.结果表明该方法缩短了全景图与点云数据融合匹配时间,并在网络环境中场景渲染帧数稳定在40帧/s以上,能够支持融合场景的高效可视化与交互分析.

Existing data fusion visualization methods have high requirements on data accuracy,complex matching process,redundant organization mode of traditional point cloud,poor dynamics for complex data and low index efficiency,and thus it is difficult to efficiently visualize multi-source data in network environment.In view of the above problems,a fast fusion visualization method of panorama and point cloud is proposed for network lightweight application.Key technologies are discussed such as two-dimensional image mapping,fast matching of three-dimensional point cloud data,optimized organization of irregular octree-based point cloud and dynamic scheduling at multiple levels of detail(LOD).A fusion-scene cross-modal interaction mechanism is designed to realize fast fusion visualization of panorama and point cloud data.Finally,a prototype system is constructed and experiments are carried out.The results show that the method reduces the time in the matching and fusion of panoramic and point cloud,and the number of frames is stable above 40 frames/s,which can support the efficient visualization and interactive analysis of fusion scenes.