Personalized 3D mannequin reconstruction based on 3D scanning

Purpose Currently, a common method of reconstructing mannequin is based on the body measurements or body features, which only preserve the body size lacking of the accurate body geometric shape information. However, the same human body measurement does not equal to the same body shape. This may result in an unfit garment for the target human body. The purpose of this paper is to propose a novel scanning-based pipeline to reconstruct the personalized mannequin, which preserves both body size and body shape information. Design/methodology/approach The authors first capture the body of a subject via 3D scanning, and a statistical body model is fit to the scanned data. This results in a skinned articulated model of the subject. The scanned body is then adjusted to be pose-symmetric via linear blending skinning. The mannequin part is then extracted. Finally, a slice-based method is proposed to generate a shape-symmetric 3D mannequin. Findings A personalized 3D mannequin can be reconstructed from the scanned body. Compared to conventional methods, the method can preserve both the size and shape of the original scanned body. The reconstructed mannequin can be imported directly into the apparel CAD software. The proposed method provides a step for digitizing the apparel manufacturing. Originality/value Compared to the conventional methods, the main advantage of the authors’ system is that the authors can preserve both size and geometry of the original scanned body. The main contributions of this paper are as follows: decompose the process of the mannequin reconstruction into pose symmetry and shape symmetry; propose a novel scanning-based pipeline to reconstruct a 3D personalized mannequin; and present a slice-based method for the symmetrization of the 3D mesh. </jats:sec

Comparison of depth cameras for three-dimensional Reconstruction in Medicine

KinectFusion is a typical three-dimensional reconstruction technique which enables generation of individual three-dimensional human models from consumer depth cameras for understanding body shapes. The aim of this study was to compare three-dimensional reconstruction results obtained using KinectFusion from data collected with two different types of depth camera (time-of-flight and stereoscopic cameras) and compare these results with those of a commercial three-dimensional scanning system to determine which type of depth camera gives improved reconstruction. Torso mannequins and machined aluminium cylinders were used as the test objects for this study. Two depth cameras, Microsoft Kinect V2 and Intel Realsense D435, were selected as the representatives of time-of-flight and stereoscopic cameras, respectively, to capture scan data for the reconstruction of three-dimensional point clouds by KinectFusion techniques. The results showed that both time-of-flight and stereoscopic cameras, using the developed rotating camera rig, provided repeatable body scanning data with minimal operator-induced error. However, the time-of-flight camera generated more accurate three-dimensional point clouds than the stereoscopic sensor. Thus, this suggests that applications requiring the generation of accurate three-dimensional human models by KinectFusion techniques should consider using a time-of-flight camera, such as the Microsoft Kinect V2, as the image capturing sensor