E-Learning is transforming the delivery of education. Today, millions of students take selfpaced online courses. However, the content and language complexity often hinders comprehension, and that with lack of immediate help from the instructor leads to weaker learning outcomes. Ability to predict difficult content in real time enables eLearning systems to adapt content as per students' level of learning. The recent introduction of lowcost eye trackers has opened a new class of applications based on eye response. Eye tracking devices can record eye response on the visual element or concept in real time. The response and the variations in eye response to the same concept over time may be indicative of the levels of learning. In this study, we have analyzed reading patterns using eye tracker and derived 12 eye response features based on psycholinguistics, contextual information processing, anticipatory behavior analysis, recurrence fixation analysis, and pupils' response. We use eye responses to predict the level of learning for a term/concept. One of the main contribution is the spatio-temporal analysis of the eye response on a term/concept to derive relevant first pass (spatial) and reanalysis (temporal) eye response features. A spatiotemporal model, built using these derived features, analyses slide images, extracts words (terms), maps the subject's eye response to words, and prepares a term-response map. A parametric baseline classifier, trained with labeled data (term-response maps) classifies a term/concept as a novel (positive class) or familiar (negative class), using majority voting method. On using, only first pass features for prediction, the baseline classifier shows 61% prediction accuracy, but on adding reanalysis features, baseline achieves 66.92% accuracy for predicting difficult terms. However, all proposed features do not have the same response to learning difficulties for all subjects, as we consider reading as an individual characteristic. Hence, we developed a non-parametric, feature weighted linguistics classifier (FWLC), which assigns weight to features based on their relevance. The FWLC classifier achieves a prediction accuracy of 90.54% an increase of 23.62% over baseline and 29.54% over the first-pass variant of baseline. Predicting novel terms as familiar is more expensive because content adapts by using this information. Hence, our primary goal is to increase the prediction rate of novel terms by minimizing the cost of false predictions. On comparing the performance of FWLC with other frequently used machine learning classifiers, FWLC achieves highest true positive rate (TPR) and lowest ratio of false negative rate (FNR) to false positive rate (FPR). The higher prediction performance of proposed spatio-temporal eye response model to predict levels of learning builds a strong foundation for eye response driven adaptive e-Learning. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Real-time eye tracking systems with human-computer interaction mechanism are being adopted to advance user experience in smart devices and consumer electronic systems. Eye tracking systems measure eye gaze and pupil response non-intrusively. This research presents an analysis of eye pupil and gaze response to video structure and content. The set of experiments for this study involved presenting different video content to subjects and measuring eye response with an eye tracker. Results show significant changes in video and scene cuts led to sharp constrictions. User response to videos can provide insights that can improve subjective quality assessment metrics. This research also presents an analysis of the pupil and gaze response to quality changes in videos. The results show pupil constrictions for noticeable changes in perceived quality and higher fixations/saccades ratios with lower quality. Using real-time eye tracking systems for video analysis and quality evaluation can open a new class of applications for consumer electronic systems. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Through eye tracking technology, scientists have explored the eyes diverse aspects and capabilities. There are many potential applications that benefit from eye tracking. Each benefit from advances in computer technology as this results in improved quality and decreased costs for eye-tracking systems.This thesis presents a computer vision-based eye tracking system for human computer interaction. The eye tracking system allows the user to indicate a region of interest in a large data space and to magnify that area, without using traditional pointer devices. Presented is an iris tracking algorithm adapted from Camshift; an algorithm originally designed for face or hand tracking. Although the iris is much smaller and highly dynamic. the modified Camshift algorithm efficiently tracks the iris in real-time. Also presented is a method to map the iris centroid, in video coordinates to screen coordinates; and two novel calibration techniques, four point and one-point calibration. Results presented show that the accuracy for the proposed one-point calibration technique exceeds the accuracy obtained from calibrating with four points. The innovation behind the one-point calibration comes from using observed eye scanning behaviour to constrain the calibration process. Lastly, the thesis proposes a non-linear visualisation as an eye-tracking application, along with an implementation.

<p>Gaze tracking is the estimation of the point in space a person is “looking at”. This is widely used in both diagnostic and interactive applications, such as visual attention studies and human-computer interaction. The most common commercial solution used to track gaze today uses a combination of infrared illumination and one or more cameras. These commercial solutions are reliable and accurate, but often expensive. The aim of this thesis is to construct a simple single-camera gaze tracker from off-the-shelf components. The method used for gaze tracking is based on infrared illumination and a schematic model of the human eye. Based on images of reflections of specific light sources in the surfaces of the eye the user’s gaze point will be estimated. Evaluation is also performed on both the software and hardware components separately, and on the system as a whole. Accuracy is measured in spatial and angular deviation and the result is an average accuracy of approximately one degree on synthetic data and 0.24 to 1.5 degrees on real images at a range of 600 mm.</p>

<p>This study is concerned with the negative effects of wearing corrective lenses while using eye trackers, and the correction of those negative effects. The eye tracker technology studied is the video based real-time Pupil Center and Corneal Reflection method. With a user study, the wearing of eyeglasses is shown to cause 20 % greater errors in the accuracy of an eye tracker than when not wearing glasses. The error is shown to depend on where on the eye tracker viewing area the user is looking.</p><p>A model for ray refraction when wearing glasses was developed. Measurements on distortions on the image of the eye caused by eyeglass lenses were carried out. The distortions were analyzed with eye tracking software to determine their impact on the image-to-world coordinates mapping. A typical dependence of 1 mm relative distance change on cornea to 9 degrees of visual field was found.</p><p>The developed mathematical/physiological model for eyeglasses focuses on artifacts not possible to accommodate for with existing calibration methods, primarily varying combinations of viewing angles and head rotations. The main unknown in the presented model is the effective strength of the glasses. Automatic identification is discussed. The model presented here is general in nature and needs to be developed further in order to be a part of a specific application.</p><p> </p>

There is much debate in the design community concerning how to make an easy-to-understand graph. While expert designers recommend including as little non-data ink as possible, there is little empirical evidence to support their arguments. Non-data ink refers to any ink on a graph that is not required to display the graph's data. As a result of the lack of strong evidence concerning how to design graphs, there is widespread confusion when it comes to best practices. This paper describes a preliminary study of graph perception and learning using an eye-tracking system at UNC's School of Information and Library Science.

I investigated the effects of probability on visual search. Previous work has shown that people can utilize spatial and sequential probability information to improve their performance on visual attention tasks. My task was a simple visual search in which the target was always present among a field of distractors, and could take one of two colors. The absolute probability of the target being either color was 0.5; however, the conditional probability – the likelihood of a particular color given a particular cue combination – varied from 0.1 to 0.9. I found that participants searched more efficiently for high conditional probability targets and less efficiently for low conditional probability targets. This modulation of efficiency was reduced or abolished when participants were not explicitly informed of the cue-target relationships. After establishing this effect, I investigated its mechanism using eye tracking methods. Early in trials, participants fixated preferentially, but not exclusively, on areas of the screen which contained predominantly stimuli of the color to which they had been cued. As the trial progressed, this color bias shifted to the target color. I conclude that search efficiency is modulated by the conditional probability of target features and that this is a top-down process that benefits from explicit knowledge of the probabilistic relationship between cues and targets, and that the modulation is a result of more efficient eye movements towards stimuli with a greater probability of being the target of search.

The accurate integration of audio-visual emotion cues is critical for social interactions and requires efficient processing of facial cues. Gaze behavior of typically developing young adults was measured via eye-tracking during the perception of dynamic audio-visual emotion (DAVE) stimuli. Participants were able to identify basic emotions (angry, fearful, happy, neutral) and determine the congruence of facial expression and prosody. Perception of incongruent videos resulted in increased reaction times and emotion identification consistent with the facial expression. Participants consistently demonstrated a featural processing approach across all tasks, with a significant preference for the eyes. Evidence of hemispheric lateralization was indicated by preferential fixation to the left (happy, angry) or right eye (fearful). Fixation patterns differed according to the facially expressed emotion, with the pattern that emerged during fearful movies supporting the significance of automatic threat processing. Finally, fixation pattern during the perception of incongruent movies varied according to task instructions.

This study is concerned with the negative effects of wearing corrective lenses while using eye trackers, and the correction of those negative effects. The eye tracker technology studied is the video based real-time Pupil Center and Corneal Reflection method. With a user study, the wearing of eyeglasses is shown to cause 20 % greater errors in the accuracy of an eye tracker than when not wearing glasses. The error is shown to depend on where on the eye tracker viewing area the user is looking. A model for ray refraction when wearing glasses was developed. Measurements on distortions on the image of the eye caused by eyeglass lenses were carried out. The distortions were analyzed with eye tracking software to determine their impact on the image-to-world coordinates mapping. A typical dependence of 1 mm relative distance change on cornea to 9 degrees of visual field was found. The developed mathematical/physiological model for eyeglasses focuses on artifacts not possible to accommodate for with existing calibration methods, primarily varying combinations of viewing angles and head rotations. The main unknown in the presented model is the effective strength of the glasses. Automatic identification is discussed. The model presented here is general in nature and needs to be developed further in order to be a part of a specific application.

Syftet med den här uppsatsen är att se hur vida digitala skärmar är ett effektivt promotionverktyg, och hur konsumenternas beteende är relaterade till denna typ av in-store promotion. Genom en explorativ studie som genomfördes på Ica Maxi Karlstad undersöktes detta fenomen med hjälp av ögonspårning och enkäter. Med denna metod kunde författarna jämföra faktorer som rör köpvanor med hur stor uppmärksamhet som riktas mot in-store elementen i en matbutik. Viktiga slutsatser pekar på att de digitala skärmar som undersökts inte bidrar med tillräckligt relevant information för att uppmärksammas av konsumenter. Resultatet visar också att digitala skärmar är något som uppmärksammas i liten skala av uppgiftsorienterade personer. Det visade sig att andra mer traditionella in-store element, som vanliga gula prisskyltar, drog mer uppmärksamhet till sig. Resultaten öppnar också upp för fortsatta studier och forskning inom området. / The purpose of this essay is to see whether digital screens are effective as promotional tools, and how consumer behavior is related to this type of in-store promotion. Through an exploratory study conducted at Ica Maxi Karlstad the phenomena was investigated by using eye-tracking and surveys. By using this method the authors could compare the factors related to shopping habits with the amount of attention given to in-store elements in a grocery store. Key findings indicate that the digital screens that were examined do not communicate enough relevant information, to gain the attention from the consumers. The results show that digital screens are something that task-oriented people pays a little attention to. It turned out that other more traditional in-store elements, such as ordinary yellow price-signs, gained more attention. Furthermore, the result opens up for further studies and research within this area.