计算机工程 ›› 2011, Vol. 37 ›› Issue (22): 171-173.doi: 10.3969/j.issn.1000-3428.2011.22.056

• 人工智能及识别技术 • 上一篇    下一篇

基于Cam加权距离的增量拉普拉斯方法

韦立庆 a,b,陈秀宏 a   

  1. (江南大学 a. 数字媒体学院;b. 物联网工程学院,江苏 无锡 214122)
  • 收稿日期:2011-05-16 出版日期:2011-11-18 发布日期:2011-11-20
  • 作者简介:韦立庆(1986-),男,硕士研究生,主研方向:模式识别,人工智能;陈秀宏,教授、博士
  • 基金项目:
    国家自然科学基金资助项目(60632050);2010年江苏省研究生创新计划基金资助项目

Incremental Laplacian Method Based on Cam Weighted Distance

WEI Li-qing a,b, CHEN Xiu-hong a   

  1. (a. School of Digital Media; b. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China)
  • Received:2011-05-16 Online:2011-11-18 Published:2011-11-20

摘要: 提出一种基于Cam加权距离的增量拉普拉斯方法。对原始数据进行拉普拉斯降维,采用Cam加权距离获得每个添加样本的近邻,由其近邻重构出降维后的插入点,更新近邻发生改变的样本点低维数据。实验结果表明,该方法在数据降维与人脸表情分类方面有较好的效果。

关键词: 特征提取, 拉普拉斯算子, Cam加权距离, 数据降维

Abstract: This paper presents an incremental Laplacian method based on Cam weighted distance. The dimension of the original data are reduced with Laplacian operator, then it obtains the neighbors of each added sample by using the Cam weighted distance and constructs the feature of the current data using such neighbors. The exisiting data embedding results are updated. Experimental results show that the method is effective on data dimension reduction and face expression classification.

Key words: feature extraction, Laplacian operator, Cam weighted distance, data dimension reduction

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