Fast neural implementation of PCA for face detectione

被引：0
|
作者：
El-Bakry, Hazem M. [1 ]
Zhao, Qiangfu [1 ]
机构：
[1] Univ Aizu, Aizu Wakamatsu 9658580, Japan
来源：
2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10 | 2006年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Principle Component Analysis (PCA) has many different important applications especially in pattern detection such as face detection / recognition. Therefore, for real time applications, the response time is required to be as very small as possible. In this paper, new implementation of PCA for fast face detection is presented. Such new implementation is designed based on cross correlation in the frequency domain between the input image and eigenvalues (weights). Simulation results show that the proposed implementation of PCA is faster than conventional one.
引用
收藏
页码：806 / +
页数：4
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