Predicting Realistic and Precise Human Body Models Under Clothing Based on Orthogonal-view Photos

The already difficult research problem becomes more challenging if the individual subjects to be modelled are dressed in normal or loose-fit clothing. In this study, we present an intelligent two-phase method to customize 3D digital human body models based on two orthogonal-view photos of the customers. It integrates both image-based and example-based modelling techniques to create human body models for individual customers with precise body measurements and realistic appearance. It fills up the research gap of human model customization; without the need of taking body scan, any customers can create their 3D digital body models only based on their orthogonal-view photos in normal or loose-fit clothing. Experimental results have shown that the proposed method can efficiently and accurately customize human models of diverse shapes, meeting the specific needs of the clothing industry.