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Fast retrieval method of three-dimensional indoor map data based on octree
LYU Hongwu, FU Junqiang, WANG Huiqiang, LI Bingyang, YUAN Quan, CHEN Shijun, CHEN Dawei
Journal of Computer Applications 2019, 39 (
1
): 82-86. DOI:
10.11772/j.issn.1001-9081.2018071646
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292
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To solve the low efficiency problem of data retrieval in indoor three-dimensional (3D) maps, an indoor 3D map data retrieval method based on octree was proposed. Firstly, the data was stored according to the octree segmentation method. Secondly, the data was encoded to facilitate addressing. Thirdly, the search data was filtered by adding a room interval constraint to the data. Finally, the indoor map data was retrieved. Compared with the search method without constraints, the search cost of the proposed method was reduced by 25 percentage points on average, and the search time was more stable. Therefore, the proposed method can significantly improve the application efficiency of indoor 3D map data.
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Classification method and updating mechanism of hierarchical 3D indoor map
FENG Guangsheng, ZHANG Xiaoxue, WANG Huiqiang, LI Bingyang, YUAN Quan, CHEN Shijun, CHEN Dawei
Journal of Computer Applications 2019, 39 (
1
): 78-81. DOI:
10.11772/j.issn.1001-9081.2018071657
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For the fact that existing map updating methods are not good at map updating in indoor map environments, a hierarchical indoor map updating method was proposed. Firstly, the activity of indoor objects was taken as a parameter. Then, the division of hierarchy was performed to reduce the amount of updated data. Finally, a Convolutional Neural Network (CNN) was used to determine the attribution level of indoor data in network. The experimental results show that compared with the version update method, the update time of the proposed method is reduced by 27 percentage points, and the update time is gradually reduced compared with the incremental update method after the update item number is greater than 100. Compared with the incremental update method, the update package size of the proposed method is reduced by 6.2 percentage points, and its update package is always smaller than that of the version update method before the data item number is less than 200. Therefore, the proposed method can significantly improve the updating efficiency of indoor maps.
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