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.

[1]  Fabio Remondino From point cloud to surface , 2003 .

[2]  Shih-Wen Hsiao,et al.  Applying Kinect on the Development of a Customized 3D Mannequin , 2015 .

[3]  J. Warren,et al.  Mean value coordinates for closed triangular meshes , 2005, SIGGRAPH 2005.

[4]  Phoebe R. Apeagyei,et al.  Application of 3D body scanning technology to human measurement for clothing Fit , 2010, J. Digit. Content Technol. its Appl..

[5]  Bugao Xu,et al.  Automatic segmenting and measurement on scanned human body , 2006 .

[6]  J. McCartney,et al.  Pattern flattening for orthotropic materials , 2005, Comput. Aided Des..

[7]  Yongsheng Ma,et al.  Garment pattern definition, development and application with associative feature approach , 2010, Comput. Ind..

[8]  Alla Sheffer,et al.  Virtual Garments: A Fully Geometric Approach for Clothing Design , 2006, Comput. Graph. Forum.

[9]  Taku Komura,et al.  Scanning and animating characters dressed in multiple-layer garments , 2017, The Visual Computer.

[10]  Charlie C. L. Wang,et al.  From laser-scanned data to feature human model: a system based on fuzzy logic concept , 2003, Comput. Aided Des..

[11]  Cynthia L. Istook,et al.  3D body scanning systems with application to the apparel industry , 2001 .

[12]  Ligang Liu,et al.  Scanning 3D Full Human Bodies Using Kinects , 2012, IEEE Transactions on Visualization and Computer Graphics.

[13]  Sung Min Kim,et al.  Garment pattern generation from body scan data , 2003, Comput. Aided Des..

[14]  Xiangyang Ju,et al.  Automatic segmentation of 3D human body scans , 2000 .

[15]  Bugao Xu,et al.  Body scanning and modeling for custom fit garments , 2002 .

[16]  Jirí Zára,et al.  Spherical blend skinning: a real-time deformation of articulated models , 2005, I3D '05.

[17]  Joseph H. Nurre,et al.  Locating landmarks on human body scan data , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[18]  Yueqi Zhong Two-step Registration in 3D Human Body Scanning Based on Multiple RGB-D Sensors , 2015 .

[19]  Dieter Fox,et al.  RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments , 2012, Int. J. Robotics Res..

[20]  Philip C. Treleaven,et al.  Building symbolic information for 3D human body modeling from range data , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[21]  Andrew W. Fitzgibbon,et al.  KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera , 2011, UIST.

[22]  Matthew Ming Fai Yuen,et al.  Feature-based reverse engineering of mannequin for garment design , 1999, Comput. Aided Des..

[23]  Matthew Ming-Fai Yuen,et al.  A semantic feature language for sculptured object modelling , 2000, Comput. Aided Des..