Animated Character Style Investigation with Decision Tree Classification

Abstract

Although animated characters are based on human features, these features are exaggerated. These exaggerations greatly differ by country, gender, and the character’s role in the story. This study investigated the characteristics of US and Japanese character designs and the similarities and differences or even the differences in exaggerations between them. In particular, these similarities and differences can be used to formulate a shared set of principles for US and Japanese animated character designs; 90 Japanese and 90 US cartoon characters were analyzed. Lengths for 20 parts of the body were obtained for prototypical real human bodies and animated characters from Japan and the United States. The distributions of lengths were determined, for all characters and for characters as segmented by country, gender, and the character’s role in the story. We also compared the body part lengths of animated characters and prototypical real human bodies, noting whether exaggerations were towards augmentation or diminishment. In addition, a decision tree classification method was used to determine the required body length parameters for identifying the classification conditions of animated characters by country, gender, and character’s role in the story. The results indicated that both US and Japanese male animated characters tend to feature exaggerations in head and body sizes, with exaggerations for US characters being more obvious. The decision tree only required five length parameters of the head and chest to distinguish between US and Japanese animated characters (accuracy = 94.48% and 67.46% for the training and testing groups, respectively). Through a decision tree method, this study quantitatively revealed the exaggeration patterns in animated characters and their differences by country, gender, and character’s role in the story. The results serve as a reference for designers and researchers of animated character model designs with regards to quantifying and classifying character exaggerations.