In this paper, we report the results of a set of psychophysical experiments that measure the perceptual strengths of videos with different combinations of blockiness, blurriness, and packet-loss artifacts and the overall annoyance. Participants were instructed to search each video for impairments and rate the strength of their individual features (artifacts). A repeated measure Anova (RM-ANOVA) performed on the data showed that artifact physical strengths have a significant effect on annoyance judgments. We tested and reported a set of linear models on the experimental data and we found that all these models give a good description of the relation between individual artifact perceptual strengths and the overall annoyance. In other words, all models presented a very good correlation with the experimental data, showing that annoyance can be modeled as a multidimensional function of the individual artifact perceptual strengths. Additionally, results show that there are interactions among artifact signals.
The thriving of online fashion markets has increasingly drawn people's attention. More and more small business owners and individual sellers have joined the traditional professional retail industry, which has led to the blooming of image-based online fashion communities and product photography. Accordingly, we have been dedicated to study how to improve the aesthetic quality of fashion images. In previous work, based on the psychophysical experiments we conducted and the aesthetics evaluation of a given collection of photos, we designed features for aesthetics inference, and introduced a SVM predictor to indicate the image quality. Using this predictor we investigate a large range of fashion photos; and our recent findings show that human aesthetic feedback on fashion images significantly depends on another two high-level factors: the nature of the background in the photo, and how the fashion items are displayed. We believe that fashion photos in which the fashion item is worn by a model, or placed on a mannequin are more aesthetically pleasing than others; and likewise people tend to prefer photos with white background. Furthermore, based on ground truth data that we collected, we perform a statistical analysis to validate these conclusions.