Crowd-powered parameter analysis for visual design exploration

Abstract

Parameter tweaking is one of the fundamental tasks in the editing of visual digital contents, such as correcting photo color or executing blendshape facial expression control. A problem with parameter tweaking is that it often requires much time and effort to explore a high-dimensional parameter space. We present a new technique to analyze such high-dimensional parameter space to obtain a distribution of human preference. Our method uses crowdsourcing to gather pairwise comparisons between various parameter sets. As a result of analysis, the user obtains a goodness function that computes the goodness value of a given parameter set. This goodness function enables two interfaces for exploration: Smart Suggestion, which provides suggestions of preferable parameter sets, and VisOpt Slider, which interactively visualizes the distribution of goodness values on sliders and gently optimizes slider values while the user is editing. We created four applications with different design parameter spaces. As a result, the system could facilitate the user's design exploration.