Literature DB >> 35702682

A comprehensive survey on techniques to handle face identity threats: challenges and opportunities.

Mayank Kumar Rusia1, Dushyant Kumar Singh1.   

Abstract

The human face is considered the prime entity in recognizing a person's identity in our society. Henceforth, the importance of face recognition systems is growing higher for many applications. Facial recognition systems are in huge demand, next to fingerprint-based systems. Face-biometric has a highly dominant role in various applications such as border surveillance, forensic investigations, crime detection, access management systems, information security, and many more. Facial recognition systems deliver highly meticulous results in every of these application domains. However, the face identity threats are evenly growing at the same rate and posing severe concerns on the use of face-biometrics. This paper significantly explores all types of face recognition techniques, their accountable challenges, and threats to face-biometric-based identity recognition. This survey paper proposes a novel taxonomy to represent potential face identity threats. These threats are described, considering their impact on the facial recognition system. State-of-the-art approaches available in the literature are discussed here to mitigate the impact of the identified threats. This paper provides a comparative analysis of countermeasure techniques focusing on their performance on different face datasets for each identified threat. This paper also highlights the characteristics of the benchmark face datasets representing unconstrained scenarios. In addition, we also discuss research gaps and future opportunities to tackle the facial identity threats for the information of researchers and readers.
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.

Entities:  

Keywords:  Authentication; Biometrics; Computer vision; Deep learning; Face recognition; Image processing; Machine learning

Year:  2022        PMID: 35702682      PMCID: PMC9183764          DOI: 10.1007/s11042-022-13248-6

Source DB:  PubMed          Journal:  Multimed Tools Appl        ISSN: 1380-7501            Impact factor:   2.577


  23 in total

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Journal:  Perception       Date:  2010       Impact factor: 1.490

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Authors:  Kevin J Zuo; Tomas J Saun; Christopher R Forrest
Journal:  Plast Reconstr Surg       Date:  2019-06       Impact factor: 4.730

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Authors:  Pradeep Buddharaju; Ioannis T Pavlidis; Panagiotis Tsiamyrtzis; Mike Bazakos
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2007-04       Impact factor: 6.226

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Authors:  A L Yuille
Journal:  J Cogn Neurosci       Date:  1991       Impact factor: 3.225

6.  Challenges in representation learning: a report on three machine learning contests.

Authors:  Ian J Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron Courville; Mehdi Mirza; Ben Hamner; Will Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; Fangxiang Feng; Ruifan Li; Xiaojie Wang; Dimitris Athanasakis; John Shawe-Taylor; Maxim Milakov; John Park; Radu Ionescu; Marius Popescu; Cristian Grozea; James Bergstra; Jingjing Xie; Lukasz Romaszko; Bing Xu; Zhang Chuang; Yoshua Bengio
Journal:  Neural Netw       Date:  2014-12-29

7.  Spontaneous Expression Recognition using Universal Attribute Model.

Authors:  Nazil Perveen; Debaditya Roy; C Krishna Mohan
Journal:  IEEE Trans Image Process       Date:  2018-07-16       Impact factor: 10.856

8.  Deep Context-Sensitive Facial Landmark Detection With Tree-Structured Modeling.

Authors:  Jiajian Zeng; Siyuan Liu; Xi Li; Debbah Abderrahmane Mahdi; Fei Wu; Gang Wang
Journal:  IEEE Trans Image Process       Date:  2018-05       Impact factor: 10.856

9.  Robust face alignment by cascaded regression and de-occlusion.

Authors:  Jun Wan; Jing Li; Zhihui Lai; Bo Du; Lefei Zhang
Journal:  Neural Netw       Date:  2019-12-20

10.  The neural plasticity of other-race face recognition.

Authors:  James W Tanaka; Lara J Pierce
Journal:  Cogn Affect Behav Neurosci       Date:  2009-03       Impact factor: 3.282

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