A Real-Time User Interest Meter Based on Human Cognitive Model and its Applications

Abstract

In this paper, we propose the Interest Meter, a system allowing computers understand users’ reactions, based on multimodal interfaces for measuring users’ in-terests in real time. The Interest Meter takes account of users’ spontaneous reactions. In this work, we analyze the variations of users’ eye movements, blinks, head motions, and facial expressions when they interact with computers. Furthermore, we propose the method of combining those signals into interest level and verify its reliability in our experiment. There are two integrated applications pre-sented in this work. First, produces each user’s personal memory according to their reactions relate to the Magic Crystal Ball. Second, from user’s reaction, automatically edits the MV-style home video during watching. Experi-mental results have showed that the Interest Meter can measure user’s interest and make a great improvement in the interaction.