3D female upper body modelling based on 2D images

Abstract

Purpose With the rapid advancement of computer information technology, the traditional clothing industry has stridden towards automation and digitization that drive the growth of electronic commerce and line retailing. The purpose of this paper is to propose an approach on 3D upper body modelling based on the body measurements extracted by non-contact anthropometry. Design/methodology/approach Based on the frontal and side images of the human body, the body sizes were extracted through silhouette extraction, identification of landmarks and girth prediction. The generation rules of 15 characteristic cross-sectional curves were established using a method “feature points – inserted points – feature curves – basic surface – mannequin”. The feature points of each position were determined at each curve, such as the side neck point, front neck point, shoulder point, bust point, and bust root point and so on to get the cross-sections, and then some feature points were inserted at the curves according to the widths and depths to establish the calculative models. For example, there are 18 points distributed at the bust cross-sectional curve to determine the shape. Findings The final mannequin could describe the basic characteristics of a human body, and the shape of the feature curves could also fit the body type to provide basis for the future research on automatic pattern generation. Originality/value This study can realize the 3D virtual modelling of female upper body and the automatic generation of the individualized apparel patterns based on the frontal and side images.

Status of research on parametric methods for the reconstruction of 3D models of the human body for virtual fitting

“…Compared with the method of reconstructing the 3D model of the human body based on the point cloud, reconstructing it based on 2D images is cheaper and the relevant data are easier to process. Many studies have considered such methods (Wei et al, 2023;Gu et al, 2020;Maken and Gupta, 2023). The main idea pursued by most researchers is to extract features from contours of the image and map them into the parameterized 3D statistical model of the human body.…”

“…Many studies have considered such methods (Wei et al. , 2023; Gu et al. , 2020; Maken and Gupta, 2023).…”

Modern Clothing Design Based on Human 3D Somatosensory Technology

“…Due to the inconsistency of the coordinate system, the occlusion of surrounding objects, and the interference of noise points, the captured depth data and skeleton data often need to be preprocessed to ensure the accuracy and precision of the data and facilitate subsequent use. The noise points of the depth data are processed by the bilateral filtering algorithm; the pose (position and orientation) of the world coordinate system is calculated, and the nearest iteration method is used for calibration; the smooth filtering algorithm is used for the Kinect skeleton [15].…”