A Real-Time Machine Learning Based Solution for Privacy Enforcement in Video Recordings and Live Streaming

These past years the world had to deal with a whole new situation brought by Covid-19. Everyone’s routine changed and we started passing way more time than before on virtual meeting, virtual chats and similar. With this, many privacy problems arised from all the video data generated by a single user. Google and Zoom introduced the possibility to blur out the background while using a front face camera, but this did not solve many privacy concerns ranging from showing people in videos without their permission, to the leaking of sensible data and information from videos uploaded online. We propose a solution build over the use of computer vision techniques like image segmentation and classification for context recognition for a privacy enforcement solution capable of fitting the user’s personal need, blurring out selectively specific objects from a video based on the user’s preferences for each room in which they are.