@inproceedings{d5e5d28921fd43bdb385cada0e6d6cd3,
title = "Subjective Assessment of Image Quality Induced Saliency Variation",
abstract = "Our previous study has shown that image distortions cause saliency distraction, and that visual saliency of a distorted image differs from that of its distortion-free reference. Being able to measure such distortion-induced saliency variation (DSV) significantly benefits algorithms for automated image quality assessment. Methods of quantifying DSV, however, remain unexplored due to the lack of a benchmark. In this paper, we build a benchmark for the measurement of DSV through a subjective study. Sixteen experts in computer vision were asked to compare saliency maps of distorted images to the corresponding saliency maps of the original images. All saliency maps were rendered from ground truth human fixations. A statistical analysis is performed to reveal the behaviours and properties of human assessment of the saliency variation. The benchmark is made publicly available to the research community.",
keywords = "Image quality, distortion, eye-tracking, saliency, visual attention",
author = "Lucie Leveque and Wei Zhang and Hantao Liu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 26th IEEE International Conference on Image Processing, ICIP 2019 ; Conference date: 22-09-2019 Through 25-09-2019",
year = "2019",
month = sep,
doi = "10.1109/ICIP.2019.8803736",
language = "English",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "1024--1028",
booktitle = "2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings",
}