International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 4 July-August 2024 Submit your research before last 3 days of August to publish your research paper in the issue of July-August.
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Volume 6 Issue 4
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Face Identification And Blurring the Face Using Deep Learning Based Approaches In Videos

Author(s) Chandan D. Sawarkar, Dr. Gurudev B. Sawarkar
Country India
Abstract In an era where privacy concerns and ethical considerations dominate technological advancements, our study presents a pioneering solution at the intersection of facial recognition and privacy preservation in video streams. By amalgamating sophisticated facial recognition algorithms from the face recognition library [1] with Gaussian blur techniques, our system redefines the landscape of real-time face recognition. Key to our approach is the judicious application of blur effects, selectively safeguarding the identities of individuals while maintaining the integrity of facial recognition processes. Through meticulous encoding and storage of known faces [2], our system seamlessly identifies familiar individuals within video data. Leveraging facial recognition capabilities [3], it swiftly discerns between known and unknown faces, ensuring that only unidentified individuals are subject to the privacy-enhancing blur treatment.
Keywords Facial recognition, Privacy preservation, Gaussian blur, Real-time video processing, Ethical innovation, Privacy-enhancing technologies
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-03-05
Cite This Face Identification And Blurring the Face Using Deep Learning Based Approaches In Videos - Chandan D. Sawarkar, Dr. Gurudev B. Sawarkar - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.14479
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.14479
Short DOI https://doi.org/gtmbh4
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E-ISSN 2582-2160
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