Customized 3D Clothes Modeling for Virtual Try-On System Based on Multiple Kinects

Most existing 3D virtual try-on systems put clothes designed in one environment on a human captured in another environment, which cause the mismatching color and brightness problem. And also typical 3D clothes modeling starts with manually designed 2D patterns, deforms them to fit on a human, and applies stitching to sew those patterns together. Such work usually relies on labor work. In this thesis, we describe an approach to reconstruct clothes and human that both are from the same space. With multiple Kinects, it models the 3D clothes directly out of a dressed mannequin without the need of the predefined 2D clothes patterns, and fits them to a human user. Our approach has several advantages: (i) a simple hardware setting consisted of multiple Kinects to capture a human model; (ii) 3D clothes modeling directly out of captured human figure. To the best of our knowledge, our work is the first one which separates clothes out of captured human figure; (iii) resizing of clothes adapting to any sized human user; (iv) a novel idea of virtual try-on where clothes and human are captured in the same location