Integrated face and facial components detection

Citation

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).

Abstract

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.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/CIMSim.2015.16
Publisher:	IEEE
Keywords:	Face detection; Facial components detection; Mean comparison; CCTV images
Depositing User:	Nabilah Mustapa
Date Deposited:	08 Apr 2019 08:31
Last Modified:	08 Apr 2019 08:31
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/CIMSim.2015.16
URI:	http://psasir.upm.edu.my/id/eprint/14337
Statistic Details:	View Download Statistic

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