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The impact of bio-inspired approaches toward the advancement of face recognition

Alsalibi, B.a, Venkat, I.a, Subramanian, K.G.a, Lutfi, S.L.a, De Wilde, P.b (2015) The impact of bio-inspired approaches toward the advancement of face recognition. ACM Computing Surveys, 48 (1). ISSN 0360-0300. (doi:10.1145/2791121) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:58006)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1145/2791121

Abstract

An increased number of bio-inspired face recognition systems have emerged in recent decades owing to their intelligent problem-solving ability, flexibility, scalability, and adaptive nature. Hence, this survey aims to present a detailed overview of bio-inspired approaches pertaining to the advancement of face recognition. Based on a well-classified taxonomy, relevant bio-inspired techniques and their merits and demerits in countering potential problems vital to face recognition are analyzed. A synthesis of various approaches in terms of key governing principles and their associated performance analysis are systematically portrayed. Finally, some intuitive future directions are suggested on how bio-inspired approaches can contribute to the advancement of face biometrics in the years to come.

Item Type: Article
DOI/Identification number: 10.1145/2791121
Additional information: cited By 0
Uncontrolled keywords: Artificial intelligence; Biometrics; Evolutionary algorithms; Feature extraction; Neural networks; Optimization; Problem solving, Bio-inspired approach; Bio-inspired computing; Bio-inspired techniques; Face recognition systems; Intelligent problems; Performance analysis; Potential problems; Swarm Intelligence, Face recognition
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Philippe De Wilde
Date Deposited: 24 Oct 2016 10:50 UTC
Last Modified: 25 Jan 2020 04:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58006 (The current URI for this page, for reference purposes)
De Wilde, P.b: https://orcid.org/0000-0002-4332-1715
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