scholarly journals Geometric Model for Human Body Orientation Classification

Author(s):  
Igi Ardiyanto
Author(s):  
Igi Ardiyanto

This  paper proposes  an approach  for cal- culating  and estimating  human body orientation  using geometric model. A novel framework integrating gradient shape and texture model of the human body orientation is proposed.  The gradient  is a natural way for describing the human  shapes, while the texture  explains the body characteristic. The framework  is then combined with the random  forest classifier to obtain a robust  class  differ- ence  of the human body orientation. Experiments and comparison results are provided to show the advantages of our system over state-of-the-art. For both modeled and un-modeled gradient-texture  features with random forest classifier, they achieve the highest accuracy on separating each human orientation   class, respectively  56.9% and 67.3% for TUD-Stadtmitte  dataset.


2021 ◽  
Author(s):  
Karam Abughalieh ◽  
Shadi Alawneh

2010 ◽  
Vol 52 (4) ◽  
pp. 281-290
Author(s):  
AKI TSURUHARA ◽  
SO KANAZAWA ◽  
MASAMI K. YAMAGUCHI
Keyword(s):  

2016 ◽  
Vol 7 ◽  
Author(s):  
Edgard Jung ◽  
Kohske Takahashi ◽  
Katsumi Watanabe ◽  
Stephan de la Rosa ◽  
Martin V. Butz ◽  
...  

2010 ◽  
Vol 8 (6) ◽  
pp. 953-953 ◽  
Author(s):  
A. Tsuruhara ◽  
S. Kanazawa ◽  
M. Yamaguchi

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