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A comparative experimental analysis of separate and combined facial features for GA-ANN based technique
conference contributionposted on 2017-12-06, 00:00 authored by Xiaolong FanXiaolong Fan, Brijesh Verma
This paper investigates a feature selection and classification technique for face recognition using genetic algorithms and artificial neural networks. The experiments using separate facial features and combined facial features have been conducted on a face image dataset which is extracted from FERET benchmark database and was used in our previous study. The experiments using just combined features have also been conducted on an extended version of this dataset. The new experiments have achieved much better recognition rate than some of the existing face recognition techniques and significantly improved our previously published results. A detailed comparative analysis of experimental results is included in this paper.
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
Number of Pages6
LocationLas Vegas, Nev.
Place of PublicationNew Jersey
External Author AffiliationsFaculty of Business and Informatics;