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.
Dettaglio pubblicazione
2024, ICYRIME 2024: 9th International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, Pages -
A Real-Time Machine Learning Based Solution for Privacy Enforcement in Video Recordings and Live Streaming (04b Atto di convegno in volume)
MANGANELLI CONFORTI Pietro, Emanuele Matteo, Mandelli Lorenzo
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