Eye tracking

About: Eye tracking is a research topic. Over the lifetime, 17102 publications have been published within this topic receiving 370872 citations. The topic is also known as: eyetracking.

Eye-tracking student's behaviour for e-learning improvement

Abstract: Nowadays, there is a shift in society towards an increased use of technological aids, which help us in our daily life tasks. However, very little of these improvements are being used in the education system, specifically to help mitigate common academic problems that affect students, such as poor performance and disengagement issues, that can arise from identifiable symptoms like changes in behaviour and emotions. In this paper an architecture to handle eye tracker data is presented, which analyses the gaze data, captured from students in learning scenarios to predict specific behaviours and issues. A scenario where distractive stimuli was used to emulate deviations in the attention levels is presented. A methodology was defined able to detect gaze patterns for further automatization of the detection of students’ issues as lack of attention and performance. The goal is in the near future to provide Learning Management Systems with solutions able to present insightful real time cognitive data of the users and automatically detect if they are exhibiting any low performance and automatically react.

Eye movement-retina delayed feedback.

Abstract: Time delays between ocular movement and retinal input have been studied by yoking a visual target to eye movement by experimental programming methods and a laboratory real-time computer system. The subject's task was to manipulate this eye movement-yoked target cursor to perform either compensatory or pursuit eye tracking. The computer thereafter was programmed to store input eye-movement signals and read them out after a delay interval to control the yoked visual target cursor controlled by the eye movements. Delay time constants of 0.1 second significantly affected tracking. Eye movement-retinal feedback delays appeared to have an even more marked effect on positive pursuit eye tracking.

Exploiting the GBVS for Saliency aware Gaze Heatmaps

Abstract: Analyzing visual perception in scene images is dominated by two different approaches: 1.) Eye Tracking, which allows us to measure the visual focus directly by mapping a detected fixation to a scene image, and 2.) Saliency maps, which predict the perceivability of a scene region by assessing the emitted visual stimulus with respect to the retinal feature extraction. One of the best-known algorithms for calculating saliency maps is GBVS. In this work, we propose a novel visualization method by generating a joint fixation-saliency heatmap. By incorporating a tracked gaze signal into the GBVS, the proposed method equilibrates the fixation frequency and duration to the scene stimulus, and thus visualizes the rate of the extracted visual stimulus by the spectator.