Optimizing human model reconstruction from RGB-D images based on skin detection

2016 ◽  
Vol 20 (3) ◽  
pp. 159-172 ◽  
Author(s):  
Guang Chen ◽  
Jituo Li ◽  
Jiping Zeng ◽  
Bei Wang ◽  
Guodong Lu
Keyword(s):  
Human Model ◽  
Skin Detection ◽  
Model Reconstruction

3D Human Model Reconstruction from Sparse Uncalibrated Views

2016 ◽  
Vol 36 (6) ◽  
pp. 46-56 ◽  
Author(s):  
Xiaoguang Han ◽  
Kwan-Yee K. Wong ◽  
Yizhou Yu
Keyword(s):  
Human Model ◽  
Model Reconstruction

scholarly journals Experimental Study of a Deep-Learning RGB-D Tracker for Virtual Remote Human Model Reconstruction

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Shahram Payandeh ◽  
Jeffrey Wael
Keyword(s):  
Experimental Study ◽  
Deep Learning ◽  
Tracking System ◽  
Living Environment ◽  
The Body ◽  
Human Model ◽  
Virtual Human ◽  
Generic Model ◽  
Model Reconstruction ◽  
Position Information

Tracking movements of the body in a natural living environment of a person is a challenging undertaking. Such tracking information can be used as a part of detecting any onsets of anomalies in movement patterns or as a part of a remote monitoring environment. The tracking information can be mapped and visualized using a virtual avatar model of the tracked person. This paper presents an initial novel experimental study of using a commercially available deep-learning body tracking system based on an RGB-D sensor for virtual human model reconstruction. We carried out our study in an indoor environment under natural conditions. To study the performance of the tracker, we experimentally study the output of the tracker which is in the form of a skeleton (stick-figure) data structure under several conditions in order to observe its robustness and identify its drawbacks. In addition, we show and study how the generic model can be mapped for virtual human model reconstruction. It was found that the deep-learning tracking approach using an RGB-D sensor is susceptible to various environmental factors which result in the absence and presence of noise in estimating the resulting locations of skeleton joints. This as a result introduces challenges for further virtual model reconstruction. We present an initial approach for compensating for such noise resulting in a better temporal variation of the joint coordinates in the captured skeleton data. We explored how the extracted joint position information of the skeleton data can be used as a part of the virtual human model reconstruction.

Comparative Psychosocial Pathology: A Human Model of Primate Abusive Behavior

1984 ◽  
Vol 29 (10) ◽  
pp. 781-782
Author(s):  
Gene P. Sackett ◽  
David V. Baldwin
Keyword(s):  
Human Model ◽  
Abusive Behavior

Real Time 2D Garment Simulation on Wireframe Human Model

2011 ◽  
Vol 4 (5) ◽  
pp. 305-308
Author(s):  
R. ANIL Kumar ◽  
◽  
R.I. Sathya R.I. Sathya
Keyword(s):  
Real Time ◽  
Human Model

2295-PUB: Impaired First-Phase Insulin Secretion Predicts the Development of Hyperglycemia in a Human Model of Acute Beta-Cell Mass Reduction

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 2295-PUB
Author(s):  
TERESA MEZZA ◽  
PIETRO MANUEL FERRARO ◽  
GIANFRANCO DI GIUSEPPE ◽  
CHIARA MARIA ASSUNTA CEFALO ◽  
SIMONA MOFFA ◽  
...  
Keyword(s):  
Insulin Secretion ◽  
Beta Cell ◽  
Cell Mass ◽  
Beta Cell Mass ◽  
Human Model ◽  
Mass Reduction ◽  
First Phase Insulin Secretion
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