Consensus Analysis and Modeling of Visual Aesthetic Perception

Abstract

This paper reports a characteristic relation between skewness and kurtosis of aesthetic score distributions in a massive photo aesthetics dataset generated from online voting. Analysis results reveal an unexpectedly wide range of kurtosis in the mediocre photo group, asymmetric consensus, the 4/3 power-law regime in both extremes, and tag-specific relation in the skewness-kurtosis plane. From the human cognition perspective on affective content analysis, these patterns are interpreted as supporting the necessity of a consensus property in addition to the preference used so far for accurate modeling of aesthetic evaluation process in human mind. For explaining the observed patterns, we propose a new computational model of a dynamic system based on the interaction between multiple attractors. Characteristic patterns in response time and consensus are predicted from the proposed model and observed in the experiments with human subjects for model validation.