计算机工程与应用Issue(11)：206-209,4.DOI:10.3778/j.issn.1002-8331.1205-0313
基于PCA和多元统计回归的人群人数统计方法
Crowd counting method based on PCA and multivariate statistical regression
摘要
Abstract
To solve the problems of the separation of segmentation characteristics and texture features in the crowd statistic, together with improving the accuracy in regression model, this paper proposes a new kind of method of crowd statistic based on PCA and multivariate statistical regression. The research takes the measure of PCA in order to reduce the dimension of the crowd prospect segmentation features and texture features which are extracted. This paper establishes a multiple linear regression model so as to determine the trend of the relationship between characteristic quantity and the number of crowd. The research modifies the Gaussian process regression model according to the trend. The experimental result shows that this method is more suitable for the statistic of large-scale crowd.关键词
人群人数统计/分割特征/纹理特征/多元线性回归/高斯过程回归Key words
crowd counting/segmentation feature/texture feature/multiple linear regression/Gaussian process regression分类
信息技术与安全科学引用本文复制引用
李虎,张二虎,段敬红..基于PCA和多元统计回归的人群人数统计方法[J].计算机工程与应用,2014,(11):206-209,4.基金项目
陕西省教育厅科研计划项目（No.12JK0736）。 （）
