Cross-Device Image Saliency Detection: Database and Comparative Analysis

While saliency detection for images has been extensively studied during the past decades, only a little work explores the influence of different viewing devices (i.e., tablet computer, mobile phone) towards human visual attention behavior. The lack of research in this field hinders the research prog...

Full description

Saved in:
Bibliographic Details
Published inVisual communications and image processing (Online) pp. 1 - 5
Main Authors Ding, Xiaoying, Yue, Guanghui, Zhang, Yingxue
Format Conference Proceeding
LanguageEnglish
Published IEEE 08.12.2024
Subjects
Behavioral sciences
cross-device
eye-tracking
Gaze tracking
Mobile handsets
Performance evaluation
Saliency detection
saliency detecton
Stability analysis
Tablet computers
visual attention
Visual communication
Visual databases
Visualization
Online AccessGet full text

Cover

More Information
Summary:While saliency detection for images has been extensively studied during the past decades, only a little work explores the influence of different viewing devices (i.e., tablet computer, mobile phone) towards human visual attention behavior. The lack of research in this field hinders the research progress in cross-device image saliency detection. In this paper, we first establish a novel cross-device saliency detection (CDSD) database based on eye-tracking experiments and investigate subjects' visual attention behavior when using different viewing devices. Then, we evaluate several classic saliency detection models using the CDSD database and the evaluation results indicate that the cross-device performance of these models need further improvement. Finally, some meaningful discussions are provided which might enlighten the design of cross-device saliency detection model. The proposed CDSD database will be made publicly available.
ISSN:2642-9357
DOI:10.1109/VCIP63160.2024.10849782