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| Formato: | Recurso digital |
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Zenodo
2025
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| Acceso en liña: | https://doi.org/10.5281/zenodo.18068708 |
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| author | Yash R. Pounikar Ayushi A. Bhadade Amit R. Khotele Yash S. Bhoyar Varun D. Khadse Bharat S. Dhak |
| author_facet | Yash R. Pounikar Ayushi A. Bhadade Amit R. Khotele Yash S. Bhoyar Varun D. Khadse Bharat S. Dhak |
| contents | This paper presents a comprehensive literature review of existing face recognition-based attendance systems and anti-spoofing techniques to identify research gaps and propose solutions. We analyze ten significant research works covering face recognition algorithms, liveness detection methods, system architectures, and deployment frameworks. Our review reveals that while individual components have been well-researched, existing systems lack comprehensive integration of high-accuracy recognition with multi-layered anti-spoofing, real-time analytics, and intelligent attendance logic in a unified framework. Most implementations focus on either recognition accuracy or liveness detection but rarely combine both effectively. We identify critical gaps including absence of intelligent check-in and check-out logic, limited real-time analytics capabilities, inadequate multi-modal liveness detection, and lack of scalable web-based architectures. Based on these findings, we propose an integrated system combining ArcFace recognition, four-layer liveness detection, Flask-based real-time streaming, PostgreSQL with intelligent attendance algorithms, and Node.js powered analytics dashboard to address identified limitations. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18068708 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A Systematic Review of Face Recognition Attendance Systems: Anti-Spoofing Integration, Intelligent Automation, and Research Gaps Yash R. Pounikar Ayushi A. Bhadade Amit R. Khotele Yash S. Bhoyar Varun D. Khadse Bharat S. Dhak face recognition attendance system literature review anti-spoofing liveness detection ArcFace research gaps proposed solution This paper presents a comprehensive literature review of existing face recognition-based attendance systems and anti-spoofing techniques to identify research gaps and propose solutions. We analyze ten significant research works covering face recognition algorithms, liveness detection methods, system architectures, and deployment frameworks. Our review reveals that while individual components have been well-researched, existing systems lack comprehensive integration of high-accuracy recognition with multi-layered anti-spoofing, real-time analytics, and intelligent attendance logic in a unified framework. Most implementations focus on either recognition accuracy or liveness detection but rarely combine both effectively. We identify critical gaps including absence of intelligent check-in and check-out logic, limited real-time analytics capabilities, inadequate multi-modal liveness detection, and lack of scalable web-based architectures. Based on these findings, we propose an integrated system combining ArcFace recognition, four-layer liveness detection, Flask-based real-time streaming, PostgreSQL with intelligent attendance algorithms, and Node.js powered analytics dashboard to address identified limitations. |
| title | A Systematic Review of Face Recognition Attendance Systems: Anti-Spoofing Integration, Intelligent Automation, and Research Gaps |
| topic | face recognition attendance system literature review anti-spoofing liveness detection ArcFace research gaps proposed solution |
| url | https://doi.org/10.5281/zenodo.18068708 |