A Software Framework for PCA-based Face Recognition

被引：4

作者：

Peng, Peng ^{[1
]}

Alencar, Paulo ^{[1
]}

Cowan, Donald ^{[1
]}

机构：

[1] Univ Waterloo, David R Cheriton Sch Comp Sci, Waterloo, ON, Canada

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE SCIENCE, TECHNOLOGY AND ENGINEERING (SWSTE 2016) | 2016年

关键词：

PCA; Face Recognition; Software engineering;

D O I：

10.1109/SWSTE.2016.11

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper focuses on a software framework to support face recognition, a specific area of image processing. For the processing approach, we use principal component analysis (PCA), a data dimensionality reduction approach. The goal of this study is to understand the entire face recognition process with PCA and to present a software framework supporting multiple variations, which can be used to help users create customized face recognition applications efficiently.

引用

页码：7 / 16

页数：10

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