A Systematic Review of Feature Dimensionality Reduction Techniques for Face Recognition Systems.
Loading...
Date
2017-09-07
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Digital Innovations & Contemp Res. In Sc., Eng & Tech.
Abstract
In this research, a comparison of the various techniques used for face recognition is shown in tabular
format to give a precise overview of what different authors have already projected in this particular
field. A systematic review of 40 journal articles pertaining to feature dimensionality reduction was
carried out. The articles were reviewed to appraise the methodology and to identify the key
parameters that were used for testing and evaluation. The dates of publication of the articles were
between 2007 and 2015. Ten percent (10%) of the articles reported the training time for their system
while twenty four percent (24%) reported their testing time. Sixty seven percent (67%) of the
reviewed articles reported the image dimension used in the research. Also, only forty eight percent
(48%) of the reviewed articles compared their result with other existing methods. The main emphasis
of this survey is to identify the major trade-offs of parameters and (or) metrics for evaluating the
performance of the techniques employed in dimensionality reduction by existing face recognition
systems. Findings from the review carried out showed that major performance metrics reported by
vast amount of researchers in this review is recognition accuracy in which eighty six percent (86%) of
the authors reported in their experiment.
Description
Keywords
Citation
Babatunde, R.S. (2017)