Learning shape-proportion relationships from labeled humanoid cartoons

Abstract

Character design artists typically use shape, pose and proportion as the first design layer to express role, physicality and personality traits. Inspired by this we approach the problem of automatic character synthesis by attempting to learn relations among the body-shape, proportions, pose, and trait labels from finished art. In our prior work [13], we have designed an online game framework to collect and analyze perception data on hundreds of humanoid characters. We clustered the labels and then established a relationship between the body shapes and the pose-proportion feature space. In this paper, we extend the work to explore partial shape synthesis of a character's torso and abdomen, given an input pose and proportion feature set. This paves the way for fully automatic character synthesis from labels. This is an improvement of our prior work, which addressed only shape classification.