Journal of Eye Movement Research

34 pages, 3613 KiB

Open AccessArticle

Understanding Consumer Perception and Acceptance of AI Art Through Eye Tracking and Bidirectional Encoder Representations from Transformers-Based Sentiment Analysis

by Tao Yu, Junping Xu and Younghwan Pan

J. Eye Mov. Res. 2024, 17(5), 1-34; https://doi.org/10.16910/jemr.17.5.3 - 22 Dec 2024

Viewed by 442

Abstract

This study investigates public perception and acceptance of AI-generated art using an integrated system that merges eye-tracking methodologies with advanced bidirectional encoder representations from transformers (BERT)-based sentiment analysis. Eye-tracking methods systematically document the visual trajectories and fixation spots of consumers viewing AI-generated artworks, elucidating the inherent relationship between visual activity and perception. Thereafter, the BERT-based sentiment analysis algorithm extracts emotional responses and aesthetic assessments from numerous internet reviews, offering a robust instrument for evaluating public approval and aesthetic perception. The findings indicate that consumer perception of AI-generated art is markedly affected by visual attention behavior, whereas sentiment analysis uncovers substantial disparities in aesthetic assessments. This paper introduces enhancements to the BERT model via domain-specific pre-training and hyperparameter optimization utilizing deep Gaussian processes and dynamic Bayesian optimization, resulting in substantial increases in classification accuracy and resilience. This study thoroughly examines the underlying mechanisms of public perception and assessment of AI-generated art, assesses the potential of these techniques for practical application in art creation and evaluation, and offers a novel perspective and scientific foundation for future research and application of AI art. Full article

► Show Figures

Figure 1

17 pages, 6603 KiB

Open AccessArticle

Impact of Leading Line Composition on Visual Cognition: An Eye-Tracking Study

by Hsien-Chih Chuang, Han-Yi Tseng and Chia-Yun Chiang

J. Eye Mov. Res. 2024, 17(5), 1-17; https://doi.org/10.16910/jemr.17.5.2 - 13 Dec 2024

Viewed by 241

Abstract

Leading lines, a fundamental composition technique in photography, are crucial to guiding the viewer’s visual attention. Leading line composition is an effective visual strategy for influencing viewers’ cognitive processes. However, in-depth research on the impact of leading line composition on cognitive psychology is lacking. This study investigated the cognitive effects of leading line composition on perception and behavior. The eye movement behaviors of 34 participants while they viewed photographic works with leading lines were monitored through eye-tracking experiments. Additionally, subjective assessments were conducted to collect the participants’ perceptions of the images in terms of aesthetics, complexity, and directional sense. The results revealed that leading lines significantly influenced the participants’ attention to key elements of the work, particularly when prominent subject elements were present. This led to greater engagement, longer viewing times, and enhanced ratings on aesthetics and directional sense. These findings suggest that skilled photographers can employ leading lines to guide the viewer’s gaze and create visually compelling and aesthetically pleasing works. This research offers specific compositional strategies for photography applications and underscores the importance of leading lines and subject elements in enhancing visual impact and artistic expression. Full article

► Show Figures

Figure 1

17 pages, 1756 KiB

Open AccessArticle

Intelligent Standalone Eye Blinking Monitoring System for Computer Users

by Ahmad A. Jiman, Amjad J. Abdullateef, Alaa M. Almelawi, Khan M. Yunus, Yasser M. Kadah, Ahmad F. Turki, Mohammed J. Abdulaal, Nebras M. Sobahi, Eyad T. Attar and Ahmad H. Milyani

J. Eye Mov. Res. 2024, 17(5), 1-17; https://doi.org/10.16910/jemr.17.5.1 - 6 Dec 2024

Viewed by 174

Abstract

Purpose: Working on computers for long hours has become a regular task for millions of people around the world. This has led to the increase of eye and vision issues related to prolonged computer use, known as computer vision syndrome (CVS). A main contributor to CVS caused by dry eyes is the reduction of blinking rates. In this pilot study, an intelligent, standalone eye blinking monitoring system to promote healthier blinking behaviors for computer users was developed using components that are affordable and easily available in the market. Methods: The developed eye blinking monitoring system used a camera to track blinking rates and operated audible, visual and tactile alarm modes to induce blinks. The hypothesis in this study is that the developed eye blinking monitoring system would increase eye blinks for a computer user. To test this hypothesis, the developed system was evaluated on 20 subjects. Results: The eye blinking monitoring system detected blinks with high accuracy (95.9%). The observed spontaneous eye blinking rate was 43.1 ± 14.7 blinks/min (mean ± standard deviation). Eye blinking rates significantly decreased when the subjects were watching movie trailers (25.2 ± 11.9 blinks/min; Wilcoxon signed rank test; p < 0.001) and reading articles (24.2 ± 12.1 blinks/min; p < 0.001) on a computer. The blinking monitoring system with the alarm function turned on showed an increase in blinking rates (28.2 ± 12.1 blinks/min) compared to blinking rates without the alarm function (25.2 ± 11.9 blinks/min; p = 0.09; Cohen’s effect size d = 0.25) when the subjects were watching movie trailers. Conclusions: The developed blinking monitoring system was able to detect blinking with high accuracy and induce blinking with a personalized alarm function. Further work is needed to refine the study design and evaluate the clinical impact of the system. This work is an advancement towards the development of a profound technological solution for preventing CVS. Full article

► Show Figures

Figure 1

Journal Menu

Journal Browser

J. Eye Mov. Res., Volume 17, Issue 5 (December 2024) – 3 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI