| 网络环境下全景图和点云数据快速融合可视化方法 |
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| 引用本文： | 朱军,陈逸东,张昀昊,黄华平,吴思豪,赵犁. 网络环境下全景图和点云数据快速融合可视化方法[J]. 西南交通大学学报, 2022, 57(1): 18-27. DOI: 10.3969/j.issn.0258-2724.20200360 |
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| 作者姓名： | 朱军 陈逸东 张昀昊 黄华平 吴思豪 赵犁 |
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| 作者单位： | 1.西南交通大学地球科学与环境工程学院，四川 成都 6117562.中铁二院工程集团有限责任公司，四川 成都 6100313.四川豪格远景市政建设有限公司，四川 成都 610036 |
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| 基金项目： | 国家自然科学基金(U2034202)；;四川省科技计划(2020JDTD0003,2019YFG0460)； |
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| 摘 要： | 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...
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| 关 键 词： | 全景图 三维点云 数据匹配 网络可视化 |
| 收稿时间： | 2020-06-08 |
Visualization Method for Fast Fusion of Panorama and Point Cloud Data in Network Environment |
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| ZHU Jun,CHEN Yidong,ZHANG Yunhao,HUANG Huaping,WU Sihao,ZHAO Li. Visualization Method for Fast Fusion of Panorama and Point Cloud Data in Network Environment[J]. Journal of Southwest Jiaotong University, 2022, 57(1): 18-27. DOI: 10.3969/j.issn.0258-2724.20200360 |
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| Authors: | ZHU Jun CHEN Yidong ZHANG Yunhao HUANG Huaping WU Sihao ZHAO Li |
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| Affiliation: | 1.Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China2.China Railway Eryuan Engineering Group Co. Ltd., Chengdu 610031, China3.Sichuan Hauge Vision Municipal Construction Co. Ltd., Chengdu 610036, China |
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| Abstract: | 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. |
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