Automatic three-dimensional-scanned garment fitting based on virtual tailoring and geometric sewing

Abstract

In this article, we presented a new automatic three-dimensional-scanned garment fitting method for A-Pose-scanned human models. Both the garment and the human body were decomposed based on feature lines defined by various landmarks. The patches of the three-dimensional garment were automatically positioned around the human model by setting up the correspondence via feature matching. Virtual sewing was engaged to obtain the final results of virtual dressing. The penetration between cloth model and human model was solved by a geometrical method constrained by Laplacian-based deformation. The experimental results indicated that the proposed method was an efficient way for redressing various garments onto various human models while maintaining the original geometrical features of garments.

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.