T-7: Assessment of Visual Signals: From Technical Quality to Aesthetic Quality: Part 1: Intro to two presenters

Image and video data account for more than 80% of big data, and the proportion is still rising. Accompanying the explosive growth of visual data, quality assessment becomes increasingly important, which has extensive applications in image/video processing, imaging system design and optimization, and smart photography. Visual quality assessment can be categorized into technical quality assessment (TQA) and aesthetic quality assessment (AQA). TQA mainly evaluates the visual distortions, including noise, sharpness, contrast change, etc. By contrast, AQA focuses on a higher level of aesthetic factors, including rule of thirds, depth of field, color harmony, etc. During recent years, both TQA and AQA have attracted wide interests. In this tutorial, we will first give a comprehensive and up-to-date review of the recent advances on image/video TQA, together with a discussion of its applications. Then, we introduce recent research progresses on AQA, including generic image aesthetic assessment (GIAA) and personalized IAA (PIAA). Especially for PIAA, we discuss two issues particularly significant to it: rating distribution prediction and personality-assisted aesthetic assessment. We will also discuss some emerging topics on TQA/AQA, including the generalization capability of quality models, the relation between TQA and AQA, as well as aesthetics-assisted image editing.