Face Identification And Bluring the Face Using Deep Learning Based Approaches In Videos

Computer Science and Engineering

User experiences, our system serves as a beacon of ethical innovation, bridging the gap between technological advancement and societal values. 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 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, our system seamlessly identifies familiar individuals within video data. Leveraging facial recognition capabilities, it swiftly discerns between known and unknown faces, ensuring that only unidentified individuals are subject to the privacy-enhancing blur treatment. This nuanced approach not only upholds the accuracy and reliability of face recognition but also prioritizes the protection of individual privacy rights.

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