Detecting eye fixations by projection clustering
Eye movements are certainly the most natural and repetitive movement of a human being. The most mundane activity, such as watching television or reading a newspaper, involves this automatic activity which consists of shifting our gaze from one point to another. Identification of the components of eye movements (fixations and saccades) is an essential part in the analysis of visual behavior because these types of movements provide the basic elements used by further investigations of human vision. However, many of the algorithms that detect fixations present a number of problems. In this article, we present a new fixation identification technique that is based on clustering of eye positions, using projections and projection aggregation applied to static pictures. We also present a new method that computes dispersion of eye fixations in videos considering a multiuser environment. To demonstrate the performance and usefulness of our approach we discuss our experimental work with two different applications: on fixed image and video.
eye fixations projected clustering algorithms static pictures videos performance experimentation interaction modeling