Cross-Device Image Saliency Detection: Database and Comparative Analysis

• Published in: Visual communications and image processing (Online) pp. 1 - 5
• Main Authors: Ding, Xiaoying, Yue, Guanghui, Zhang, Yingxue
• Format: Conference Proceeding
• Language: English
• 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
• DOI: 10.1109/VCIP63160.2024.10849782

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.