- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | 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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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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