计算机工程Issue(10)：172-175,180,5.DOI:10.3969/j.issn.1000-3428.2013.10.036
基于概率密度和轮廓的三维模型检索
3D Model Retrieval Based on Probability Density and Contour
摘要
Abstract
Aiming at incomprehensive description of 3D model of Silhouette descriptor(SIL) and Density-Based Framework(DBF), this paper proposes a new 3D model retrieval algorithm: Density-based Contour(DBC). It characterizes a 3D object using multivariate probability functions of the object’s 2D contours’ features. Two models can be compared by the similarity of their 2D contours’ probability functions. The new algorithm performs better than SIL on describing contours of the model and it also shows stronger resistance to noise than DBF. The retrieval performance on PSB shows that DBC has a higher retrieval accuracy comparing to other traditional state-of-the-art 3D model retrieval algorithms.关键词
三维模型检索/轮廓/概率密度函数/核密度估计/特征描述/匹配不变性Key words
3D model retrieval/contour/probability density function/kernel density estimation/feature description/matching invariance分类
信息技术与安全科学引用本文复制引用
唐祺,杨新..基于概率密度和轮廓的三维模型检索[J].计算机工程,2013,(10):172-175,180,5.基金项目
国家“973”计划基金资助项目(2010CB732500) （2010CB732500）
