Integrated face and facial components detection

This paper presents an algorithm that detects faces and facial features (eyes, nose and mouth) on images captured by CCTV system under various imaging conditions, such as variation in poses, scale, illumination and occlusion. The system detects face, nose and mouth using three different classifiers,...

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Main Authors: Ho, Lip Chin, Hanafi, Marsyita, Salka, Tanko Danial
Format: Conference or Workshop Item
Language:English
Published: IEEE 2015
Online Access:http://psasir.upm.edu.my/id/eprint/14337/1/Integrated%20face%20and%20facial%20components%20detection.pdf
http://psasir.upm.edu.my/id/eprint/14337/
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spelling my.upm.eprints.143372019-04-08T08:31:45Z http://psasir.upm.edu.my/id/eprint/14337/ Integrated face and facial components detection Ho, Lip Chin Hanafi, Marsyita Salka, Tanko Danial This paper presents an algorithm that detects faces and facial features (eyes, nose and mouth) on images captured by CCTV system under various imaging conditions, such as variation in poses, scale, illumination and occlusion. The system detects face, nose and mouth using three different classifiers, which were created based on the Viola-Jones method [1] and the eyes were detected using an Eye Detection method that consists of resolution reduction, identification of the eye candidates using eye filter [2] and eyes localization based on mean comparison. Experimented on 500 images, the algorithm produced 98.4% accuracy for face, 98.8% for nose, 95.6% for mouth and 94.8% for eyes. IEEE 2015 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/14337/1/Integrated%20face%20and%20facial%20components%20detection.pdf Ho, Lip Chin and Hanafi, Marsyita and Salka, Tanko Danial (2015) Integrated face and facial components detection. In: 2015 Seventh International Conference on Computational Intelligence, Modelling and Simulation (CIMSim 2015), 27-29 July 2015, Kuantan, Pahang, Malaysia. (pp. 87-91). 10.1109/CIMSim.2015.16
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper presents an algorithm that detects faces and facial features (eyes, nose and mouth) on images captured by CCTV system under various imaging conditions, such as variation in poses, scale, illumination and occlusion. The system detects face, nose and mouth using three different classifiers, which were created based on the Viola-Jones method [1] and the eyes were detected using an Eye Detection method that consists of resolution reduction, identification of the eye candidates using eye filter [2] and eyes localization based on mean comparison. Experimented on 500 images, the algorithm produced 98.4% accuracy for face, 98.8% for nose, 95.6% for mouth and 94.8% for eyes.
format Conference or Workshop Item
author Ho, Lip Chin
Hanafi, Marsyita
Salka, Tanko Danial
spellingShingle Ho, Lip Chin
Hanafi, Marsyita
Salka, Tanko Danial
Integrated face and facial components detection
author_facet Ho, Lip Chin
Hanafi, Marsyita
Salka, Tanko Danial
author_sort Ho, Lip Chin
title Integrated face and facial components detection
title_short Integrated face and facial components detection
title_full Integrated face and facial components detection
title_fullStr Integrated face and facial components detection
title_full_unstemmed Integrated face and facial components detection
title_sort integrated face and facial components detection
publisher IEEE
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/14337/1/Integrated%20face%20and%20facial%20components%20detection.pdf
http://psasir.upm.edu.my/id/eprint/14337/
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score 13.160551