3D face recognition: A comprehensive survey in 2022

Jing, Yaping; Lu, Xuequan; Gao, Shang

doi:10.1007/s41095-022-0317-1

Cited by 12 publications

(2 citation statements)

References 157 publications

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“…3D face recognition is more accurate than 2D face recognition: Jing, Y et al [1] comprehensively explain 3D face recognition, attributing face geometry and deep learning as the main drive for new developments. The use of A.I.…”

Section: Literature Reviewmentioning

confidence: 99%

Improved Face Authentication by Constructing an Adjustable 3D Image from two 2D Images taken by Two Adjacent Cameras

Domb

2024

IJLERA

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With the vast spread of automation, the significant demand for communication services, adding IoT to the Internet, and the corresponding huge increase and sophistication in malicious attacks utilizing system vulnerabilities to penetrate systems. Identification and Authentication are heavily used in every access trial towards any electronic resource and communication networks. The traditional approach to coping with such challenges is using passwords, encryption, Secure ID, Firewall, Etc. More safety methods use Biometrics, which suffer from spoofing. The access control market is a fast-growing and highly volatile market that poses significant challenges for investors seeking to make secured decisions. As the market continues to evolve and become more mainstream, there is a growing demand for new identification and authentication technologies. This paper proposes expanding the number of features extracted from a 3D image, with unique features evolved during the generation of the 3D image of the prospect at the access control stage. We mounted two identical 2D cameras on the same bar, allowing the adjustment of the distance between the two mounted cameras. The two cameras are simultaneously activated, generating a unique 3D image, including some distortion. This stage is executed at the person enrollment process and repeated at the access stage, providing an enhanced, unique, and cannot be faked Authentication. Experiments support the proposed approach.

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Section: Literature Reviewmentioning

confidence: 99%

Improved Face Authentication by Constructing an Adjustable 3D Image from two 2D Images taken by Two Adjacent Cameras

Domb

2024

IJLERA

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“…However, the models suggested are limited in scope and do not encompass the entire CF field. Therefore, other researchers [42,43] point out the need for a unified model to include all CF terms with an organized data collection process [44]. These works collectively offer a foundation for the CFMM development and integration.…”

Section: B Cloud Nmi and Compliance Frameworkmentioning

confidence: 99%

An Improved Machine Learning Method by applying Cloud Forensic Meta-Model to Enhance the Data Collection Process in Cloud Environments

Al-mugern,

Othman,

Al-Dhaqm

2024

Eng. Technol. Appl. Sci. Res.

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Cloud computing has revolutionized the way businesses operate by offering accuracy in Normalized Mutual Information (NMI). However, with the growing adoption of cloud services, ensuring the accuracy and validation of common processes through machine learning and clustering of these common concepts as well as of the processes generated by cloud forensics experts’ data in cloud environments has become a paramount concern. The current paper proposes an innovative approach to enhance the data collection procedure in cloud environments by applying a Cloud Forensic Meta-Model (CFMM) and integrating it with machine learning techniques to improve the cloud forensic data. Through this approach, consistency and compatibility across different cloud environments in terms of accuracy are ensured. This research contributes to the ongoing efforts to validate the clustering process for data collection in cloud computing environments and advance the field of cloud forensics for standardizing the representation of cloud forensic data, certifying NMI and accuracy across different cloud environments.

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Constructing and Processing 3D Face Structures Using Structure of Motion Without Complex Instruments

Mittal,

Rathore,

Garg

2024

Lecture Notes in Networks and Systems

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3D face recognition: A comprehensive survey in 2022

Cited by 12 publications

References 157 publications

Improved Face Authentication by Constructing an Adjustable 3D Image from two 2D Images taken by Two Adjacent Cameras

Improved Face Authentication by Constructing an Adjustable 3D Image from two 2D Images taken by Two Adjacent Cameras

An Improved Machine Learning Method by applying Cloud Forensic Meta-Model to Enhance the Data Collection Process in Cloud Environments

Constructing and Processing 3D Face Structures Using Structure of Motion Without Complex Instruments

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