International Journal on Science and Technology

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Photo Retrieval System based on Face Recognition with Cloud Integration

Author(s) Kritika Patidar, Kaushal Rathore, Divya Kumawat, Mandakini Ingle, Gajendra Singh Rajput
Country India
Abstract Event photography is the process of capturing images of personal or public event in order to preserve memories. Using AI and cloud storage, this study streamline and accelerate the process of locating, sharing, and managing event photographs in real-time. Without need of manual sorting, users can easily retrieve their photos, due to online storage, QR code login, and facial recognition technology.
In this paper we have implemented FaceNet AI model to locate attendees’ photos without going through numerous images. Our model has achieved 90% accuracy for single-face recognition and average 78% accuracy in group photos, where lighting and varied angles impacted performance. We have used AWS S3 provides scalable cloud storage for event images, while PostgreSQL securely manages user data and photo metadata. This research project focuses on implementing the use of access control measure, and regulations such as General Data Protection Regulation (GDPR), to safeguard user information’s it uses QR code-based authentication to ensure authorized access to images. Furthermore, it proposes strategies for enhancing the system’s balance and dependability. This technology uses AI, cloud storage, and real-time image processing to make event photography easier for both attendees and professional photographers. Events are made more memorable by automating the photo-finding process and enhancing user experience and security.
Keywords Event Photography, FaceNet, Facial Recognition, Cloud Storage, QR Code.
Field Engineering
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-06-15
DOI https://doi.org/10.71097/IJSAT.v16.i2.5091
Short DOI https://doi.org/g9qqxb
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