Video Face Anonymization for Preserving Privacy
G. Megala, Ramarathnam Venkatesan, T. Vigneshwaran · 2022
This work scales with the development of preserving privacy on face anonymization in a video. The aim of this work is to identify, preserve and protect the privacy of individuals who appear in videos with sensitive contexts or wish to conceal their identities before sharing on social media platforms to avoid cyber bullying, cyber stalking and other problems caused by the trend of viral videos in today’s social climate. An automatic face detection is implemented and blurring for processing the video. The experimental results shows that person face privacy is preserved temporal in appearance across video frames.