I. Introduction
The history of eye-tracking goes back to the 19th century when scientists tried to study the reading process by direct observation [1], [2]. Along with the development of eye-tracking equipment, experimental studies in psychology and engineering have taken advantage of this new form of implicit human feedback opting for the day that every screen will have an affordable embedded eye-tracker. Some approaches to exploit this implicit feedback can be found in [3]–[8]. In this paper we discuss the use of eye-trackers for image annotation in the field of multimedia and vision to classify images as a function of the target template that guides user visual attention implicitly, promptly and accurately.