Management algorithm of point-cloud data based on octree concerned with adaptive levels of detail

被引：0

作者：

Zhang J. ^{[1
,2
]}

Xu D. ^{[1
]}

Wang X. ^{[1
]}

机构：

[1] School of Resource and Environment, North China University of Water Resources and Electric Power, Zhengzhou

[2] Key Laboratory of Geo-special Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu

来源：

Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | 2016年 / 51卷 / 01期

关键词：

Levels of detail; Octree; Point cloud; Simulation error; Visibility culling;

D O I：

10.3969/j.issn.0258-2724.2016.01.012

中图分类号：

学科分类号：

摘要：

Large-scale point-cloud data are not easy to organize effectively and have great redundancy at dynamic visualization, and it is hard to realize the adaptive display. Aiming at these problems, a new algorithm concerned with the levels of detail (LOD) of point-cloud expression on the basis of octree structure was proposed. The algorithm assigned every scanning point into an octree node, and integrated top-down division with down-top calculation as the pretreatment strategy to reduce the amount of real-time calculation. Then it made any region meet the accuracy requirement and display speed automatically by building conservative simulation-error evaluation criteria. Furthermore, with the help of acceleration methods, large-scale point-cloud data could be organized effectively and expressed smoothly with little data redundancy. Preliminary experiments show that the algorithm has abilities to overcome the shortcoming of the classical R-tree methods; meanwhile, with the support of optimized pretreatment and assistant acceleration methods, the amount of real-time calculation is small and the time of each frame can hold within 0.04 s easily. © 2016, Editorial Department of Journal of Southwest Jiaotong University. All right reserved.

引用

页码：78 / 84

页数：6

共 13 条

[1]

Li D., 3D visualization of geospatial information: graphics based or imagery based, Acta Geodaetica et Cartographica Sinic, 39, 2, pp. 111-114, (2010)

[2]

Zhang F., Huang X., Li D., Spherical projection based triangulation for one station terrestrial laser scanning point cloud, Acta Geodaetica et Cartographica Sinica, 38, 1, pp. 48-54, (2009)

[3]

Zhang J., Yao Z., LOD algorithm of terrain based on conservative screen error and isolated division of quad-tree, Journal of Southwest Jiaotong University, 48, 4, pp. 666-671, (2013)

[4]

Mandow A., Martinez J.L., Reina A., Et al., Fast range-independent spherical subsampling of 3D laser scanner points and data reduction performance evaluation for scene registration, Pattern Recognition Letters, 31, 11, pp. 1239-1250, (2010)

[5]

Zheng K., Zhu L., Wu X., Et al., Study on spatial indexing techniques for 3D GIS, Geography and Geo-information Science, 22, 4, pp. 35-39, (2006)

[6]

Zhu Q., Gong J., Zhang Y., An efficient 3D R-tree spatial index method for virtual geographic environment, ISPRS Journal of Photogrammetry & Remote Sensing, 62, 3, pp. 217-224, (2007)

[7]

Gong J., Zhu Q., Zhang Y., Et al., An efficient 3D R-tree extension method concerned with levels of detail, Acta Geodaetica et Cartographica Sinica, 40, 2, pp. 249-255, (2011)

[8]

Gong J., Zhu Q., Zhang H., Et al., An adaptive control method of LODs for 3D scene based on R-tree index, Acta Geodaetica et Cartographica Sinica, 40, 4, pp. 531-534, (2011)

[9]

Pffiffr N., A subdivision algorithm for smooth 3D terrain models, ISPRS Journal of Photogrammetry & Remote Sensing, 59, 3, pp. 115-127, (2005)

[10]

Renato P., Fastmesh: efficient view-dependent meshing, Proceedings of 2001 International Conference on Computer Graphics & Applications, pp. 22-30, (2001)

← 1 2 →