Abstract
Live-feeling communication is a seamless process of intelligent system estimating user intention solely on passive user-to-robot communication of user emotions and body movements. In this paper we study the live-feeling communication in an entertainment framework; a real-time streaming event (football) is split into set of important and relevant scenes, and for each scene the user intention is estimated. For each scene the amount of desired details and the desired content is estimated. In order to obtain the best possible estimation result we predict the user intention for each scene using a set of different predictors by using a parameter search approach. We show that using the collected data certain situations can be estimated with accuracy of up to 95% while others are still beyond the reach of the used prediction algorithms.