Visual Design Exploration with Crowd-Powered Parameter Analysis

Abstract

Parameter tweaking is one of the fundamental tasks in the editing of visual digital contents, such as correcting photo color. A problem with parameter tweaking is that it often requires much time and effort to explore a high-dimensional parameter space. To facilitate such exploration, we first present a new technique to analyze a parameter space to obtain a distribution of human preference. Our technique uses crowdsourced human computation to collect data for analysis. As a result of this analysis, the user obtains a goodness function that computes the goodness value of a given parameter set. This goodness function enables two user 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 applied our technique to four applications with different design parameter spaces.