Level-of-interest estimation for personalized TV program recommendation

Abstract

We describe a prototype system that analyzes video from a camera mounted on a TV receiver or set-top-box, showing viewers watching the TV. The system recognizes the faces of registered viewers, and estimates the level of interest that each viewer displays in the program being viewed. This information, along with receiver operation history, can be used to build viewer profiles and to offer personalized program recommendations reflecting each viewer's perceived interests.