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计算机工程 ›› 2009, Vol. 35 ›› Issue (4): 183-186. doi: 10.3969/j.issn.1000-3428.2009.04.065

• 人工智能及识别技术 • 上一篇    下一篇

基于随机分布估计的点云密度提取

叶爱芬,龚声蓉,王朝晖,刘纯平   

  1. (苏州大学计算机科学与技术学院,苏州 215006)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-02-20 发布日期:2009-02-20

Point Cloud Density Extraction Based on Stochastic Distribution Estimation

YE Ai-fen, GONG Sheng-rong, WANG Zhao-hui, LIU Chun-ping   

  1. (School of Computer Science & Technology, Soochow University, Suzhou 215006 )
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-02-20 Published:2009-02-20

摘要: 针对目前密度提取方法提取的密度信息不能表现点云局部分布信息和分布随机性的缺陷,提出结合随机分布估计的密度提取方法。该方法采用分块计数法得到每个小分块的密度,结合点云总体的密集度得到一个能够反映点云局部积聚特征的参数,为判别点云分布的随机性、均匀性等提供较好的特征依据。

关键词: 离散点云, 点云密度, 点云随机分布估计

Abstract: Density extraction method has difficulty in representing local distribution and its stochastic feature from the extracted density information. This paper proposes a solution to solve this problem, combing density method with stochastic distribution estimation. The method computes the density of each single small plot, and combines it with the overall density of the point cloud. A parameter is obtained, which can reflect the local aggregation feature. Tests show that this parameter can satisfactorily provide reliable data on estimating stochastic distribution and homogeneity of the point cloud.

Key words: scattered point cloud, point cloud density, stochastic distribution estimation of point cloud

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