NDLI: Face Detection Based on Template Matching and 2DPCA Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Wang, Jizeng Yang, Hongmei
Copyright Year	2008
Abstract	Human face recognition technology is a popular research topic in the biometrics identification area. Face detection is the most important pre-processing module of a face recognition system, and it plays an important role in applications such as video surveillance, human computer interface. The purpose of the face detection is to search and orient faces in images in complex background. In this paper, we propose a hierarchical face detection method by using the template matching algorithm and 2DPCA algorithm. The method includes two different classifiers. The first one is called rough classifier, which filtrates the most of the non-face. The second one is a core classifier, which uses 2DPCA algorithm to detect the face based on the result from the first classifier. The results of the experiment indicates that we implement hierarchical detection to face images not only improves the accurate rate of the face detection, but also shortens detection time greatly.
Starting Page	575
Ending Page	579
File Size	1022323
Page Count	5
File Format	PDF
ISBN	9780769531199
DOI	10.1109/CISP.2008.270
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biometrics Computer vision Image recognition Eyes Face recognition face detection Humans template matching Face detection Signal processing algorithms face recognition Feature extraction 2DPCA Biomedical signal processing
Content Type	Text
Resource Type	Article

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