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Face detection using artificial neural network approach

A frontal face detection system using artificial neural network is presented. The system used integral image for image representation which allows fast computation of the features used. The system also applies the adaboost learning algorithm to select a small number of critical visual features from...

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Main Authors: Khalid, Marzuki, Jumari, Khairol Faisal, Nazeer, Shahrin Azuan, Omar, Nazaruddin
Format: Article
Published: IEEE Computer Society 2007
Subjects:
Q Science (General)
Online Access:http://eprints.utm.my/id/eprint/8769/
http://doi.ieeecomputersociety.org/10.1109/AMS.2007.38
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id my.utm.8769
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spelling my.utm.87692017-10-19T03:44:30Z http://eprints.utm.my/id/eprint/8769/ Face detection using artificial neural network approach Khalid, Marzuki Jumari, Khairol Faisal Nazeer, Shahrin Azuan Omar, Nazaruddin Q Science (General) A frontal face detection system using artificial neural network is presented. The system used integral image for image representation which allows fast computation of the features used. The system also applies the adaboost learning algorithm to select a small number of critical visual features from a very large set of potential features. Besides that, it also used cascade of classifiers algorithm which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions. Furthermore, a set of experiments in the domain of face detection is presented. The system yields a promising face detection performance. IEEE Computer Society 2007 Article PeerReviewed Khalid, Marzuki and Jumari, Khairol Faisal and Nazeer, Shahrin Azuan and Omar, Nazaruddin (2007) Face detection using artificial neural network approach. First Asia International Conference On Modeling & Simulation (AMS 2007) . pp. 394-399. http://doi.ieeecomputersociety.org/10.1109/AMS.2007.38 10.1109/AMS.2007.38
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Q Science (General)
spellingShingle Q Science (General)
Khalid, Marzuki
Jumari, Khairol Faisal
Nazeer, Shahrin Azuan
Omar, Nazaruddin
Face detection using artificial neural network approach
description A frontal face detection system using artificial neural network is presented. The system used integral image for image representation which allows fast computation of the features used. The system also applies the adaboost learning algorithm to select a small number of critical visual features from a very large set of potential features. Besides that, it also used cascade of classifiers algorithm which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions. Furthermore, a set of experiments in the domain of face detection is presented. The system yields a promising face detection performance.
format Article
author Khalid, Marzuki
Jumari, Khairol Faisal
Nazeer, Shahrin Azuan
Omar, Nazaruddin
author_facet Khalid, Marzuki
Jumari, Khairol Faisal
Nazeer, Shahrin Azuan
Omar, Nazaruddin
author_sort Khalid, Marzuki
title Face detection using artificial neural network approach
title_short Face detection using artificial neural network approach
title_full Face detection using artificial neural network approach
title_fullStr Face detection using artificial neural network approach
title_full_unstemmed Face detection using artificial neural network approach
title_sort face detection using artificial neural network approach
publisher IEEE Computer Society
publishDate 2007
url http://eprints.utm.my/id/eprint/8769/
http://doi.ieeecomputersociety.org/10.1109/AMS.2007.38
_version_ 1643645066983505920
score 13.211869

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