首页> 外文期刊>IEEE Transactions on Pattern Analysis and Machine Intelligence >Equivalence of Some Common Linear Feature Extraction Techniques for Appearance-Based Object Recognition Tasks
【24h】

Equivalence of Some Common Linear Feature Extraction Techniques for Appearance-Based Object Recognition Tasks

机译:基于外观的对象识别任务的一些常见线性特征提取技术的等效性

获取原文
获取原文并翻译 | 示例

摘要

Recently, a number of empirical studies have compared the performance of PCA and ICA as feature extraction methods in appearance-based object recognition systems, with mixed and seemingly contradictory results. In this paper, we briefly describe the connection between the two methods and argue that whitened PCA may yield identical results to ICA in some cases. Furthermore, we describe the specific situations in which ICA might significantly improve on PCA.
机译:最近,许多实证研究已经将PCA和ICA作为基于外观的对象识别系统中的特征提取方法的性能进行了比较,得出的结果混合且看似矛盾。在本文中,我们简要描述了这两种方法之间的联系,并认为在某些情况下,增白的PCA可能产生与ICA相同的结果。此外,我们描述了ICA可能会显着改善PCA的特定情况。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号