Estimating intervals of interest during TV viewing for automatic personal preference acquisition

Abstract

The demand for information services considering personal preferences is increasing. In this paper, aiming at the development of a system for automatically acquiring personal preferences from TV viewers' behaviors, we propose a method for automatically estimating TV viewers' intervals of interest based on temporal patterns in facial changes with Hidden Markov Models. Experimental results have shown that the proposed method was able to correctly estimate intervals of interest with a precision rate of 86.6% and a recall rate of 80.6%. © Springer-Verlag Berlin Heidelberg 2006.