Facial plastic surgery and face recognition algorithms: Interaction and challenges. A scoping review and future directions
Face recognition (FR) technology can be used in wide range of applications such as identity authentication, access control, and surveillance. Interests and research activities in face recognition have increased significantly over the past twenty years. Plastic surgery procedures can significantly al...
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| Veröffentlicht in: | Journal of stomatology, oral and maxillofacial surgery Jg. 121; H. 6; S. 696 - 703 |
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Elsevier Masson SAS
01.12.2020
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| Abstract | Face recognition (FR) technology can be used in wide range of applications such as identity authentication, access control, and surveillance. Interests and research activities in face recognition have increased significantly over the past twenty years. Plastic surgery procedures can significantly alter facial appearance, thereby posing a serious challenge even to the state-of-the-art face matching algorithms. The purpose of this work was to detail the interaction between facial plastic surgery and facial recognition software and discuss the new challenges of this interaction.
The authors critically reviewed the literature from January 2000 to September 2019, to identify articles reporting interactions between facial plastic surgery and facial recognition algorithms and discuss the new challenges of these interactions. Controlled vocabulary terms and keywords were used in the search strategy and two authors independently analyzed data. Factors included in the analysis were: Author, Journal, Year, Scope, Study design, Plastic surgery, Data (volume, origin and processing), Identification accuracy and Conclusion (interaction/challenge).
Forty-three research articles underwent data extraction and 28 articles were included in quantitative synthesis. Of the 28 articles, the most common study designs were experimental evaluation (n=15, 53,5%), Evaluation Study studies (n=7, 25%) and Review studies (n=4, 14,3%). Fifty percent of the articles have been published in the last 4 years (14 articles, 50%). Most of the study scope was informatics (64,3%). Only 10 articles were published in medical journals. Rhytidectomy (face lift) is the most challenging procedure for the FR algorithms. Data volume varied from 4 to 2878 subjects. The proposed algorithms provide at least 15 to 99% better identification performance. Among these, only two papers discuss the new challenges of the interaction between facial plastic surgery and Face Recognition Algorithms.
In the context of advances in artificial intelligence, Internet connectivity and data integration, the purpose of this review is, to look forward to analyze the new interactions of facial plastic surgery and facial recognition algorithms, and to suggest avenues for future research and clinical application of this technology. Furthermore, to evaluate if plastic surgeons are prepared to discuss this technology with their patients. Plastic surgeons should be prepared to answer questions from patients about the fundamentals of facial recognition technology, and the potential effects of plastic surgery on facial recognition technology performance. Continued efforts are needed to provide scientifically rigorous data of facial biometric identification after facial plastic surgery and to include these notions in the routine consultation or consent process for patients seeking aesthetic facial surgery. |
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| AbstractList | Face recognition (FR) technology can be used in wide range of applications such as identity authentication, access control, and surveillance. Interests and research activities in face recognition have increased significantly over the past twenty years. Plastic surgery procedures can significantly alter facial appearance, thereby posing a serious challenge even to the state-of-the-art face matching algorithms. The purpose of this work was to detail the interaction between facial plastic surgery and facial recognition software and discuss the new challenges of this interaction.
The authors critically reviewed the literature from January 2000 to September 2019, to identify articles reporting interactions between facial plastic surgery and facial recognition algorithms and discuss the new challenges of these interactions. Controlled vocabulary terms and keywords were used in the search strategy and two authors independently analyzed data. Factors included in the analysis were: Author, Journal, Year, Scope, Study design, Plastic surgery, Data (volume, origin and processing), Identification accuracy and Conclusion (interaction/challenge).
Forty-three research articles underwent data extraction and 28 articles were included in quantitative synthesis. Of the 28 articles, the most common study designs were experimental evaluation (n=15, 53,5%), Evaluation Study studies (n=7, 25%) and Review studies (n=4, 14,3%). Fifty percent of the articles have been published in the last 4 years (14 articles, 50%). Most of the study scope was informatics (64,3%). Only 10 articles were published in medical journals. Rhytidectomy (face lift) is the most challenging procedure for the FR algorithms. Data volume varied from 4 to 2878 subjects. The proposed algorithms provide at least 15 to 99% better identification performance. Among these, only two papers discuss the new challenges of the interaction between facial plastic surgery and Face Recognition Algorithms.
In the context of advances in artificial intelligence, Internet connectivity and data integration, the purpose of this review is, to look forward to analyze the new interactions of facial plastic surgery and facial recognition algorithms, and to suggest avenues for future research and clinical application of this technology. Furthermore, to evaluate if plastic surgeons are prepared to discuss this technology with their patients. Plastic surgeons should be prepared to answer questions from patients about the fundamentals of facial recognition technology, and the potential effects of plastic surgery on facial recognition technology performance. Continued efforts are needed to provide scientifically rigorous data of facial biometric identification after facial plastic surgery and to include these notions in the routine consultation or consent process for patients seeking aesthetic facial surgery. Face recognition (FR) technology can be used in wide range of applications such as identity authentication, access control, and surveillance. Interests and research activities in face recognition have increased significantly over the past twenty years. Plastic surgery procedures can significantly alter facial appearance, thereby posing a serious challenge even to the state-of-the-art face matching algorithms. The purpose of this work was to detail the interaction between facial plastic surgery and facial recognition software and discuss the new challenges of this interaction.INTRODUCTIONFace recognition (FR) technology can be used in wide range of applications such as identity authentication, access control, and surveillance. Interests and research activities in face recognition have increased significantly over the past twenty years. Plastic surgery procedures can significantly alter facial appearance, thereby posing a serious challenge even to the state-of-the-art face matching algorithms. The purpose of this work was to detail the interaction between facial plastic surgery and facial recognition software and discuss the new challenges of this interaction.The authors critically reviewed the literature from January 2000 to September 2019, to identify articles reporting interactions between facial plastic surgery and facial recognition algorithms and discuss the new challenges of these interactions. Controlled vocabulary terms and keywords were used in the search strategy and two authors independently analyzed data. Factors included in the analysis were: Author, Journal, Year, Scope, Study design, Plastic surgery, Data (volume, origin and processing), Identification accuracy and Conclusion (interaction/challenge).MATERIAL AND METHODSThe authors critically reviewed the literature from January 2000 to September 2019, to identify articles reporting interactions between facial plastic surgery and facial recognition algorithms and discuss the new challenges of these interactions. Controlled vocabulary terms and keywords were used in the search strategy and two authors independently analyzed data. Factors included in the analysis were: Author, Journal, Year, Scope, Study design, Plastic surgery, Data (volume, origin and processing), Identification accuracy and Conclusion (interaction/challenge).Forty-three research articles underwent data extraction and 28 articles were included in quantitative synthesis. Of the 28 articles, the most common study designs were experimental evaluation (n=15, 53,5%), Evaluation Study studies (n=7, 25%) and Review studies (n=4, 14,3%). Fifty percent of the articles have been published in the last 4 years (14 articles, 50%). Most of the study scope was informatics (64,3%). Only 10 articles were published in medical journals. Rhytidectomy (face lift) is the most challenging procedure for the FR algorithms. Data volume varied from 4 to 2878 subjects. The proposed algorithms provide at least 15 to 99% better identification performance. Among these, only two papers discuss the new challenges of the interaction between facial plastic surgery and Face Recognition Algorithms.RESULTSForty-three research articles underwent data extraction and 28 articles were included in quantitative synthesis. Of the 28 articles, the most common study designs were experimental evaluation (n=15, 53,5%), Evaluation Study studies (n=7, 25%) and Review studies (n=4, 14,3%). Fifty percent of the articles have been published in the last 4 years (14 articles, 50%). Most of the study scope was informatics (64,3%). Only 10 articles were published in medical journals. Rhytidectomy (face lift) is the most challenging procedure for the FR algorithms. Data volume varied from 4 to 2878 subjects. The proposed algorithms provide at least 15 to 99% better identification performance. Among these, only two papers discuss the new challenges of the interaction between facial plastic surgery and Face Recognition Algorithms.In the context of advances in artificial intelligence, Internet connectivity and data integration, the purpose of this review is, to look forward to analyze the new interactions of facial plastic surgery and facial recognition algorithms, and to suggest avenues for future research and clinical application of this technology. Furthermore, to evaluate if plastic surgeons are prepared to discuss this technology with their patients. Plastic surgeons should be prepared to answer questions from patients about the fundamentals of facial recognition technology, and the potential effects of plastic surgery on facial recognition technology performance. Continued efforts are needed to provide scientifically rigorous data of facial biometric identification after facial plastic surgery and to include these notions in the routine consultation or consent process for patients seeking aesthetic facial surgery.CONCLUSIONIn the context of advances in artificial intelligence, Internet connectivity and data integration, the purpose of this review is, to look forward to analyze the new interactions of facial plastic surgery and facial recognition algorithms, and to suggest avenues for future research and clinical application of this technology. Furthermore, to evaluate if plastic surgeons are prepared to discuss this technology with their patients. Plastic surgeons should be prepared to answer questions from patients about the fundamentals of facial recognition technology, and the potential effects of plastic surgery on facial recognition technology performance. Continued efforts are needed to provide scientifically rigorous data of facial biometric identification after facial plastic surgery and to include these notions in the routine consultation or consent process for patients seeking aesthetic facial surgery. |
| Author | Khochtali, H. Bouguila, J. |
| Author_xml | – sequence: 1 givenname: J. surname: Bouguila fullname: Bouguila, J. organization: Department of ENT and Maxillofacial Surgery, La Rabta academic Hospital, 1007 Tunis-Tunisia, Tunis, Tunisia – sequence: 2 givenname: H. surname: Khochtali fullname: Khochtali, H. organization: Department of Maxillofacial and Aesthetic surgery, Sahloul academic Hospital, Sousse, Tunisia |
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| Keywords | Plastic surgery Face recognition Face Biometry |
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| Title | Facial plastic surgery and face recognition algorithms: Interaction and challenges. A scoping review and future directions |
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