Why is quality estimation judgment fast? Comparison of gaze control strategies in quality and difference estimation tasks

Abstract

Abstract. To understand the viewing strategies employed in a quality estimation task, we compared two visual tasks-quality estimation and difference estimation. The estimation was done for a pair of natural images having small global changes in quality. Two groups of observers estimated the same set of images, but with different instructions. One group estimated the difference in quality and the other the difference between image pairs. The results demonstrated the use of different visual strategies in the tasks. The quality estimation was found to include more visual planning during the first fixation than the difference estimation, but afterward needed only a few long fixations on the semantically important areas of the image. The difference estimation used many short fixations. Salient image areas were mainly attended to when these areas were also semantically important. The results support the hypothesis that these tasks' general characteristics (evaluation time, number of fixations, area fixated on) show differences in processing, but also suggest that examining only single fixations when comparing tasks is too narrow a view. When planning a subjective experiment, one must remember that a small change in the instructions might lead to a noticeable change in viewing strategy. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

The Fewer Reasons, the More You Like It! How Decision-Making Heuristics of Image Quality Estimation Exploit the Content of Subjective Experience

“…Future research should focus on the factors that determine these reasons in different contexts. Earlier studies suggest that attentional processes are important, both bottom-up controlled processes that are related to visual saliency and top-down processes that are based on semantics and task interpretations (Radun et al, 2014(Radun et al, , 2016.…”