Abstract
Despite the development of user-friendly interfaces for modeling garments and putting them onto characters, preparing a character dressed in multiple layers of garments can be very time-consuming and tedious. In this paper, we propose a novel scanning-based solution for modeling and animating characters wearing multiple layers of clothes. This is achieved by making use of real clothes and human bodies. We first scan the naked body of a subject by an RGBD camera, and a statistical body model is fit to the scanned data. This results in a skinned articulated model of the subject. The subject is then asked to put on one piece of garment after another, and the articulated body model dressed up to the previous step is fit to the newly scanned data. The new garment is segmented in a semi-automatic fashion and added as an additional layer to the multi-layer garment model. During runtime, the skinned character is controlled based on the motion capture data and the multi-layer garment model is controlled by blending the movements computed by physical simulation and linear blend skinning, such that the cloth preserves its shape while it shows realistic physical motion. We present results where the character is wearing multiple layers of garments including a shirt, coat and a skirt. Our framework can be useful for preparing and animating dressed characters for computer games and films.
Pengpeng Hu
Assistant Professor
Pengpeng Hu is currently an Assistant Professor with the Center for Computational Science and Mathematical Modeling, Coventry University, Coventry, U.K. He was a Senior Researcher with the Department of Electronics and Informatics, Vrije Universiteit Brussel (VUB), Brussels, Belgium. In 2016, he was a Visiting Scholar with the School of Informatics, Edinburgh University, Edinburgh, U.K. In 2017, he was a Post-Doctoral Fellow with the Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, U.K. Since 2018, he has been with VUB. His current research interests include biometrics, geometric deep learning, 3-D human body reconstruction, point cloud processing, and measurement.