Estimating the Residual Space between the Surfaces of Clothing and Human Body

2014 ◽  
Vol 556-562 ◽  
pp. 4705-4708
Author(s):  
Yi Jun Zhang ◽  
Yue Qi Zhong ◽  
Ji Ji ◽  
Zhen Wang ◽  
Yu Xiao Ji
Keyword(s):  
Noise Reduction ◽  
Surface Reconstruction ◽  
Thermal Insulation ◽  
Human Body ◽  
Point Cloud ◽  
3D Scanning ◽  
Air Gap ◽  
Fashion Design ◽  
Residual Space ◽  
Geomagic Software

This paper presented a method for measuring the residual space between clothing and human body based on 3D scanning devices. In data collecting procedure, the 3D scanning devices were used to collect original point cloud of apparels and human body. The Geomagic software was used to process the noise reduction and surface reconstruction. In measuring procedure, the volume was calculated by algorithm. Therefore, we can get the value of the residual space between clothing and human body.These residual space is called air gap. Thickness of the air gap is closely related to thermal insulation properties [1] and thermal wet comfort performance of clothing. Meanwhile, the stress levels of apparels on human body can be determined through observation [2], so this technology can be used in the field of fashion design. In addition, 3D virtual try-on system is one of the applications with important value [3].

3D Human Body Data Acquisition and Fit Evaluation of Clothing

2014 ◽  
Vol 989-994 ◽  
pp. 4161-4164 ◽  
Author(s):  
Zhen Wang ◽  
Yue Qi Zhong ◽  
Kai Jie Chen ◽  
Jia Yi Ruan ◽  
Jin Cheng Zhu
Keyword(s):  
Data Acquisition ◽  
Human Body ◽  
Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Clothing Design ◽  
Online Sales ◽  
Kinect Camera ◽  
Distribution Features ◽  
Residual Space

This paper presents the method of 3D human body data acquisition based on 3D scanning and the non-contact fit evaluation of clothing based on the distribution features of residual space between clothing and human body. A Kinect camera is employed to collect point cloud data. The points cloud is treated by Geomagic for noise reduction and surface reconstruction. By analyzing the residual space between clothing and human body, the fit distribution of scanned clothing can be achieved. The fit evaluation will make contributions to clothing design, online sales of clothing and virtual try-on.

Surface reconstruction from point cloud of human body by clustering

2006 ◽  
Vol 37 (11) ◽  
pp. 44-56 ◽  
Author(s):  
Takuya Funatomi ◽  
Isao Moro ◽  
Shinobu Mizuta ◽  
Michihiko Minoh
Keyword(s):  
Surface Reconstruction ◽  
Human Body ◽  
Point Cloud

scholarly journals A Lightweight Surface Reconstruction Method for Online 3D Scanning Point Cloud Data Oriented toward 3D Printing

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Buyun Sheng ◽  
Feiyu Zhao ◽  
Xiyan Yin ◽  
Chenglei Zhang ◽  
Hui Wang ◽  
...  
Keyword(s):  
3D Printing ◽  
Surface Reconstruction ◽  
Point Cloud ◽  
Reconstruction Algorithm ◽  
3D Scanning ◽  
Reconstruction Method ◽  
Point Cloud Data ◽  
Registration Method ◽  
Cloud Data ◽  
Web Environment

The existing surface reconstruction algorithms currently reconstruct large amounts of mesh data. Consequently, many of these algorithms cannot meet the efficiency requirements of real-time data transmission in a web environment. This paper proposes a lightweight surface reconstruction method for online 3D scanned point cloud data oriented toward 3D printing. The proposed online lightweight surface reconstruction algorithm is composed of a point cloud update algorithm (PCU), a rapid iterative closest point algorithm (RICP), and an improved Poisson surface reconstruction algorithm (IPSR). The generated lightweight point cloud data are pretreated using an updating and rapid registration method. The Poisson surface reconstruction is also accomplished by a pretreatment to recompute the point cloud normal vectors; this approach is based on a least squares method, and the postprocessing of the PDE patch generation was based on biharmonic-like fourth-order PDEs, which effectively reduces the amount of reconstructed mesh data and improves the efficiency of the algorithm. This method was verified using an online personalized customization system that was developed with WebGL and oriented toward 3D printing. The experimental results indicate that this method can generate a lightweight 3D scanning mesh rapidly and efficiently in a web environment.

scholarly journals Computational Geometry-Based Surface Reconstruction for Volume Estimation: A Case Study on Magnitude-Frequency Relations for a LiDAR-Derived Rockfall Inventory

2021 ◽  
Vol 10 (3) ◽  
pp. 157
Author(s):  
Paul-Mark DiFrancesco ◽  
David A. Bonneau ◽  
D. Jean Hutchinson
Keyword(s):  
Computational Geometry ◽  
Surface Reconstruction ◽  
Power Law ◽  
Point Cloud ◽  
Point Clouds ◽  
Volume Estimation ◽  
Estimation Methods ◽  
Small Scale ◽  
Reconstruction Methods ◽  
3D Volume

Key to the quantification of rockfall hazard is an understanding of its magnitude-frequency behaviour. Remote sensing has allowed for the accurate observation of rockfall activity, with methods being developed for digitally assembling the monitored occurrences into a rockfall database. A prevalent challenge is the quantification of rockfall volume, whilst fully considering the 3D information stored in each of the extracted rockfall point clouds. Surface reconstruction is utilized to construct a 3D digital surface representation, allowing for an estimation of the volume of space that a point cloud occupies. Given various point cloud imperfections, it is difficult for methods to generate digital surface representations of rockfall with detailed geometry and correct topology. In this study, we tested four different computational geometry-based surface reconstruction methods on a database comprised of 3668 rockfalls. The database was derived from a 5-year LiDAR monitoring campaign of an active rock slope in interior British Columbia, Canada. Each method resulted in a different magnitude-frequency distribution of rockfall. The implications of 3D volume estimation were demonstrated utilizing surface mesh visualization, cumulative magnitude-frequency plots, power-law fitting, and projected annual frequencies of rockfall occurrence. The 3D volume estimation methods caused a notable shift in the magnitude-frequency relations, while the power-law scaling parameters remained relatively similar. We determined that the optimal 3D volume calculation approach is a hybrid methodology comprised of the Power Crust reconstruction and the Alpha Solid reconstruction. The Alpha Solid approach is to be used on small-scale point clouds, characterized with high curvatures relative to their sampling density, which challenge the Power Crust sampling assumptions.

Sign in / Sign up

Export Citation Format

Share Document