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http://dx.doi.org/10.7848/ksgpc.2015.33.5.437

Improving Performance of File-referring Octree Based on Point Reallocation of Point Cloud File  

Han, Soohee (Dept. of Geoinformatics Engineering, Kyungil University)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.33, no.5, 2015 , pp. 437-442 More about this Journal
Abstract
Recently, the size of point cloud is increasing rapidly with the high advancement of 3D terrestrial laser scanners. The study aimed for improving a file-referring octree, introduced in the preceding study, which had been intended to generate an octree and to query points from a large point cloud, gathered by 3D terrestrial laser scanners. To the end, every leaf node of the octree was designed to store only one file-pointer of its first point. Also, the point cloud file was re-constructed to store points sequentially, which belongs to a same leaf node. An octree was generated from a point cloud, composed of about 300 million points, while time was measured during querying proximate points within a given distance with series of points. Consequently, the present method performed better than the preceding one from every aspect of generating, storing and restoring octree, so as querying points and memorizing usage. In fact, the query speed increased by 2 times, and the memory efficiency by 4 times. Therefore, this method has explicitly improved from the preceding one. It also can be concluded in that an octree can be generated, as points can be queried from a huge point cloud, of which larger than the main memory.
Keywords
LiDAR; 3D Point Cloud; Query; Octree; File-referring;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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