scholarly journals Human Body Shape Prediction and Analysis Using Predictive Clustering Tree

2011 ◽  
Author(s):  
Pengcheng Xi ◽  
Hongyu Guo ◽  
Chang Shu
Keyword(s):  
Human Body ◽  
Body Shape ◽  
Shape Prediction ◽  
Clustering Tree

Video-Based Human Motion Analysis

2011 ◽  
Vol 403-408 ◽  
pp. 2593-2597
Author(s):  
Hong Bao ◽  
Zhi Min Liu
Keyword(s):  
Motion Analysis ◽  
Human Body ◽  
Body Shape ◽  
Human Motion ◽  
Random Motion ◽  
Human Motion Analysis ◽  
Mass Center ◽  
Shape Features ◽  
Skeleton Model ◽  
Regular Motion

In the analysis of human motion, movement was divided into regular motion (such as walking and running) and random motion (such as falling down).Human skeleton model is used in this paper to do the video-based analysis. Key joints on human body were chosen to be traced instead of tracking the entire human body. Shape features like mass center trajectory were used to describe the movement, and to classify human motion. desired results achieved.

scholarly journals Robust Pose Estimation for Human Body Hidden with a Cover Using Body Shape Feature Obtained by Normal Vector

2014 ◽  
Vol 80 (12) ◽  
pp. 1166-1175
Author(s):  
Yuta KUDO ◽  
Takehiko SASHIDA ◽  
Yoshimitsu AOKI
Keyword(s):  
Pose Estimation ◽  
Human Body ◽  
Body Shape ◽  
Normal Vector ◽  
Shape Feature

3D description of the human body shape: application of Karhunen-Loève expansion to the CAESAR database

2002 ◽  
pp. 571-576 ◽  
Author(s):  
Zouhour Ben Azouz ◽  
Marc Rioux ◽  
Richard Lepage
Keyword(s):  
Human Body ◽  
Body Shape

scholarly journals The aging human body shape

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Alexander Frenzel ◽  
Hans Binder ◽  
Nadja Walter ◽  
Kerstin Wirkner ◽  
Markus Loeffler ◽  
...  
Keyword(s):  
Human Body ◽  
Body Shape

scholarly journals Human Body Shape Reconstruction from Binary Image Using Convolutional Neural Network

2020 ◽  
Vol 1624 ◽  
pp. 052002
Author(s):  
Jiayu Chen ◽  
Yueqi Zhong ◽  
Zhicai Yu
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Human Body ◽  
Body Shape ◽  
Shape Reconstruction ◽  
Binary Image

New human body shape descriptor based on anthropometrics points

2014 ◽  
Author(s):  
Moez Hamad ◽  
Sebastien Thomassey ◽  
Pascal Bruniaux
Keyword(s):  
Human Body ◽  
Body Shape ◽  
Shape Descriptor

Parametric Human Body Model for Digital Apparel Design

2013 ◽  
Vol 365-366 ◽  
pp. 121-124
Author(s):  
Shu Xia Wang ◽  
Sheng Feng Qin ◽  
Cong Ying Guan ◽  
Sui Huai Yu
Keyword(s):  
Cross Section ◽  
Human Body ◽  
Body Shape ◽  
Body Part ◽  
The Body ◽  
Human Model ◽  
Body Model ◽  
Key Points ◽  
Cloud Points ◽  
Body Scanner

With the advance in 3D body scanning technology, it opens opportunities for virtual try-on and automatic made-to-measure in apparel products domain. This paper proposed a novel feature-based parametric method of human body shape from the cloud points of 3D body scanner [T2. Firstly, we improved the skeleton construction through adding and adjusting the position of joints. Secondly, automatic extraction approach of semantic feature cross-sections is developed based on the hierarchy. According to the unique distribution of cloud points of each cross-section of each body part, the extraction method of key points on the cross-section is described. Thirdly, we presented an interpolation approach of key points which fit cardinal spline to cross-section for each body part, in which tension parameter is used to represent the simple deformation of body shape. Finally, a connection approach of body part is proposed by sharing a boundary curve. The proposed method has been tested with our virtual human model (VHM) system which is robust and easier to use. The process generally requires about five minutes for generating a full body model that represents the body shape captured by 3D body scanner. The model can be imported in a CAD environment for application to a wide variety of ergonomic analyses.

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