Two interfaces for visual design exploration that are realized by our analysis technique. (Top) Smart Suggestion: The user can obtain appropriate parameter sets as suggestions. (Bottom) VisOpt Slider: The user can adjust each parameter effectively by the visualization (Vis) near the slider and the optimization (Opt) that gently guides the current parameters to the optimal direction.
Two interfaces for visual design exploration that are realized by our analysis technique. (Left) Smart Suggestion: The user can obtain appropriate parameter sets as suggestions. (Right) VisOpt Slider: The user can adjust each parameter effectively by the visualization (Vis) near the slider and the optimization (Opt) that gently guides the current parameters to the optimal direction.
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.
Overview of our method. Our goal is to facilitate design exploration, which often requires to tweak many design parameters. Our method analyzes the design parameter space and obtains a so-called goodness function that can evaluate the goodness of each design. To do this, we use crowdsourced human computation. Finally, we provide two interfaces utilizing this goodness function.
Application to color correction of photos. The user can easily tweak parameters such as brightness, contrast, etc.
Application to shader. Even non-expert can easily achieve realistic stainless teapot using complex shader.
Application to camera and light control in 3D scene. Our analysis successfully captures the non-linear relationship between camera and light.
Application to facial expression modeling (blendshape). Even when there are over 50 parameters, our analysis is still powerful.
Yuki Koyama, Daisuke Sakamoto, and Takeo Igarashi. 2014. Crowd-powered parameter analysis for visual design exploration. In Proceedings of the 27th annual ACM symposium on User interface software and technology (UIST '14). ACM, New York, NY, USA, 65-74. [doi]
Yuki Koyama is funded by JSPS research fellowship. This work was supported by JSPS KAKENHI Grant Number 26-8574, 26240027. The face model is provided by faceshift AG under CC BY 3.0. The dragon and bunny models are provided by The Stanford 3D Scanning Repository.