To enhance the convenience of human body 3D modelling, this study proposes a low-cost method for 3D body reconstruction under limited views, aiming to easily acquire client body size information through smart phone photography. The human body photos of the front, side and back view are captured, and background removal is performed using the U2-Net human segmentation model. The PIFuHD model is utilised to obtain single-view point cloud patches, which are then mapped onto 2D images. A point cloud registration approach that incorporates regional segmentation and contour supervision is employed to reconstruct a complete human body model. B-spline curves are employed to fit key girths for obtaining perimeter measurements, and the effectiveness of girth measurements is validated using body data from 80 subjects. The results indicate that the proposed method exhibits closer proximity to manual measurements compared to 3D scanning, with average absolute errors within 2 cm.
Keywords: Body reconstruction; apparel customisation; body modelling; limited views; point clouds registration.
To meet the increasing demand for 3D human models in the clothing customisation field, this paper proposes a novel low-cost 3D human reconstruction method that achieves results closer to manual measurements than those obtained from 3D scanners. This method provides a convenient and feasible solution for human body modelling in garment customisation enterprises, thereby enhancing efficiency and quality in customised clothing production.