Browsing by Subject "Eye tracking"

Now showing 1 - 2 of 2

Open Access
Eye tracking using markov models
(IEEE, 2004) Bağcı, A. M.; Ansari, R.; Khokhar, A.; Çetin, A. Enis
We propose an eye detection and tracking method based on color and geometrical features of the human face using a monocular camera. In this method a decision is made on whether the eyes are closed or not and, using a Markov chain framework to model temporal evolution, the subject's gaze is determined. The method can successfully track facial features even while the head assumes various poses, so long as the nostrils are visible to the camera. We compare our method with recently proposed techniques and results show that it provides more accurate tracking and robustness to variations in view of the face. A procedure for detecting tracking errors is employed to recover the loss of feature points in case of occlusion or very fast head movement. The method may be used in monitoring a driver's alertness and detecting drowsiness, and also in applications requiring non-contact human computer interaction.
Open Access
Using eye tracking to understand the impact of visual complexity and perceptual fluency on viewers’ aesthetic preferences
(2024-09) Beder, Dilara
This study investigates the interplay between cognitive styles, visual complexity, and aesthetic evaluations in environmental psychology and architectural design, utilizing Gestalt principles. Our research was divided into two studies. In Study I, we examined the aesthetic evaluations of 24 two-dimensional geometric stimuli, manipulated using the Gestalt principles of similarity based on color and shape differences, with 39 participants. In Study II, we focused on architectural façades and used 24 two-dimensional stimuli, manipulated through the Gestalt principles of similarity and proximity, to assess aesthetic evaluations with 79 participants. Participants were classified as Field Dependent or Field Independent using the Hidden Figures Test. Additionally, we collected their aesthetic evaluations through questionnaires, supported by eye-tracking data to assess visual attention. Study I revealed a U-shaped relationship between visual complexity and aesthetic evaluations, with both low and high complexity stimuli rated higher than medium complexity ones. Study II found an inverse relationship between complexity and aesthetic ratings, with simpler façades generally preferred. Gestalt principles significantly influenced aesthetic judgments, with shape-based similarity rated higher than color-based similarity for geometric designs, and proximity-based façades rated higher than similarity-based façades in architectural contexts. Although cognitive styles did not significantly impact overall aesthetic evaluations, nuanced differences were identified in the responses of Field Dependent participants when comparing proximity-based to similarity-based designs. Gaze metrics data indicated that higher complexity levels led to more fixations and shorter fixation durations, reflecting more extensive visual exploration. These findings offer insights into how cognitive styles, complexity, and Gestalt principles shape aesthetic perceptions, informing design practices to enhance user experience.