中国机械工程2012，Vol.23Issue(15)：1833-1839,7.
基于多尺度张量分解的点云结构特征提取
Structural Feature Extraction from Point Clouds Based on Multi--scale Tensor Decomposition
摘要
Abstract
To solve the conflicts between the ability of weak feature extraction and noise resistency of traditional algorithms, a new feature extraction algorithm was proposed based on multi--scale ten- sor decomposition. Firstly, feature saliency encoding was defined based on the singular value decom- position of tensor matrix. Secondly, normal(tangential) consistent measure was constructed and used to determine the maxmuim scale combined with Romanovskii criterion. The reliability of the feature reconizing algorithm is improved. Finaly, the feature lines were constructed using minimal spanning forest. Expremental results reveal the weak feature extraction and noise resistency abilities of the method.关键词
多尺度分析/张量分解/点云/特征提取Key words
multi-- scale analysis/tensor decomposition/point cloud/feature extraction分类
信息技术与安全科学引用本文复制引用
林洪彬,刘彬,张玉存..基于多尺度张量分解的点云结构特征提取[J].中国机械工程,2012,23(15):1833-1839,7.基金项目
国家科技重大专项 （）
河北省自然科学基金资助项目 （）
河北省科学技术研究与发展计划资助项目（102121527 （）
秦皇岛市科学技术研究与发展计划资助项目 （）
河北省重点实验室开放基金资助项目 （）
