Gait Recognition with Multiple-Temporal-Scale 3D Convolutional Neural Network

Author(s):  
Beibei Lin ◽  
Shunli Zhang ◽  
Feng Bao
2020 ◽  
Author(s):  
Habiba Arshad ◽  
Muhammad Attique Khan ◽  
Muhammad Irfan Sharif ◽  
Mussarat Yasmin ◽  
João Manuel R. S. Tavares ◽  
...  

2018 ◽  
Vol 7 (4.11) ◽  
pp. 202 ◽  
Author(s):  
Mohd Shahrum Md Guntor ◽  
Rohilak Sahak ◽  
Azlee Zabidi ◽  
Nooritawati Md Tahir ◽  
Ihsan Mohd Yassin ◽  
...  

Biometric identification systems have recently made exponential advancements in term of complexity and accuracy in recognition for security purposes and a variety of other application. In this paper, a Convolutional Neural Network (CNN) based gait recognition system using Microsoft Kinect skeletal joint data points is proposed for human identification. A total of 23 subjects were used for the experiments. The subjects were positioned 45 degrees (oblique view) from Kinect. A CNN based on the modified AlexNet structure was used to fit the different input data size. The results indicate that the training and testing accuracies were 100% and 69.6% respectively.  


2019 ◽  
Vol 29 (9) ◽  
pp. 2708-2719 ◽  
Author(s):  
Noriko Takemura ◽  
Yasushi Makihara ◽  
Daigo Muramatsu ◽  
Tomio Echigo ◽  
Yasushi Yagi

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