Game creators always use prefabricated models as non-player characters (NPCs) to create an atmosphere for game scenes. However, players are likely to see different NPCs with the same 3D models because creators usually cannot prepare a high number of NPC models for big game scenes. In this article, we present an anime-like character customization system, where each customizing parameter can adjust the shape or color for the corresponding part of the character model. Based on this system, we propose an improved approach for generating a rich variety of 3D anime-like NPCs including body models and clothing items in different styles. We introduce a neural network to control the facial appearances, Gaussian mixture models to control the colors of hair and clothes, and a Bayesian network to control the outfits of clothing items. We demostrate that the proposed approach can maintain the variety and stability of the generated characters.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.