SURVEY OF EXISTING FACE RECOGNITION APPROACHES, TECHNIQUES AND CHALLENGES
- Authors
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K.F. AKINGBADE
Federal University of Technology, Akure, Nigeria
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- Keywords:
- Face Recognition, Principal Component Analysis, Eigenface, Linear Discriminant Analysis, Fisherface, Independent Component Analysis, Neural Network
- Abstract
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Abstract – Face recognition is a prominent field in signal processing analysis and has received considerable attention over the past decade due to its very diverse domains of application. The potential it has, led researchers and marketers in the industry to put effort into developing what would be an optimal approach and method that would eliminate all existing challenges encountered so far. These past works include knowledge and researches from pattern recognition, psychology neuroscience, computer vision, image processing, and machine learning. A lot of published papers focused on explaining ways to overcome difference factors (such as illumination, expression and occlusion) and attain better recognition rate. A robust technique against uncontrolled practical cases with different factors simultaneously still need to be researched upon. This paper presents some of the existing approaches, techniques and challenges associated with existing face recognition systems.
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- Published
- 2020-11-25
- Section
- Articles
- License
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Copyright
With the submission of a manuscript, the corresponding author confirms that the manuscript is not under consideration by another journal. With the acceptance of a manuscript, the Journal reserves the exclusive right of publication and dissemination of the information contained in the article. The veracity of the paper and all the claims therein is solely the opinion of the authors not the journal.
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