Monozygotic twin face recognition: An in-depth analysis and plausible improvements
Monozygotic twins, commonly known as identical twins, share extreme facial resemblance that they deceive the majority of the prevailing face recognition systems. Hence, the facial recognition systems, which are turning out to be exploited in almost all real-life biometric authentication-needing appl...
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| Published in: | Image and vision computing Vol. 116; p. 104331 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01-12-2021
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Monozygotic twins, commonly known as identical twins, share extreme facial resemblance that they deceive the majority of the prevailing face recognition systems. Hence, the facial recognition systems, which are turning out to be exploited in almost all real-life biometric authentication-needing applications, require significant upgradation to cope with this great challenge. This paper pays special attention towards categorizing and investigating the existing research on the facial recognition of monozygotic twins in an exhaustive sense. Subsequently, the research gap is analyzed. It is then followed by the description of the possible refinements, like the choice of feature and other methodological advancements, which may aid in augmenting the twin recognition accuracy of the face recognition systems. It is believed that the outcomes of the review can well-support and pave the way for further research in the future. Consequently, the “Double Trouble” posed on the commercial face recognition systems can be effectively evaded.
•Deeply examines the past research on the face recognition of identical twins.•Performs categorization of the past research.•Examines the research gap and provides possible ways to improve recognition.•Suggests a prospective system for twin face recognition.•Attracts readers and experts of facial recognition systems. |
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| ISSN: | 0262-8856 1872-8138 |
| DOI: | 10.1016/j.imavis.2021.104331 |