tailieunhanh - Aesthetic Visual Quality Assessment of Paintings

The forms are abstract, yet we see a living being present. He looks up expectantly and somewhat fearfully as his eyes are surrounded in a blue mask-like form, with wide black bands above forming the eyebrows. The eyes are beautifully, sensitively carved and seem to emerge from the soft flesh of the lids which have a very sharp, exact edge. Why does he have this disagreeable expression? He does not like the world—has too much contempt. Looking at the mask upside down, what do we see?—another very different living thing—which is smiling! On this upside-down mask we actually see three faces, one above the other, totem-pole fashion | REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER DOUBLE-CLICK HERE TO EDIT 1 Aesthetic Visual Quality Assessment of Paintings Congcong Li Student Member IEEE and Tsuhan Chen Fellow IEEE Abstract This paper aims to evaluate the aesthetic visual quality of a special type of visual media digital images of paintings. Assessing the aesthetic visual quality of paintings can be considered a highly subjective task. However to some extent certain paintings are believed by consensus to have higher aesthetic quality than others. In this paper we treat this challenge as a machine learning problem in order to evaluate the aesthetic quality of paintings based on their visual content. We design a group of methods to extract features to represent both the global characteristics and local characteristics of a painting. Inspiration for these features comes from our prior knowledge in art and a questionnaire survey we conducted to study factors that affect human s judgments. We collect painting images and ask human subjects to score them. These paintings are then used for both training and testing in our experiments. Experiment results show that the proposed work can classify high-quality and low-quality paintings with performance comparable to humans. This work provides a machine learning scheme for the research of exploring the relationship between aesthetic perceptions of human and the computational visual features extracted from paintings. Index Terms Visual Quality Assessment Aesthetics Feature Extraction Classification I. Introduction The booming development of digital media has changed the modern life a lot. It not only introduces more approaches for human to see and feel about the world but also changes the ways that computer sees and feels . It raises a group of interesting topics about allowing a computer to see and feel as human beings. For example in the field of compression lots of metrics have been proposed to allow a computer to evaluate the visual quality of .