Automated age regression for personalized IPTV services

The increasing penetration rates of high speed broadband networks have infused strong impetus for IPTV adoption and usage. One of the more intriguing possibilities of personalizing the IPTV experience is to install automated age classification capabilities onto a display set. This allows the detection, by vision-based methods, of the demographic profile of the IPTV user and automatically suggest or stream services, advertisements and adjust settings to provide a personalized IPTV experience to the user. We describe a vision-based age estimation system, capable of estimating the age of a person using the near frontal face with a mean average error of 4.64 years, using various proposed techniques such as facial alignment and hierarchical manifold-based regression. We discuss the likely scenarios where such a capability can be applied, and the likely impact it will have on the user experience. Finally, the paper explores related user issues and the possible solutions within the IPTV context.