Convolutional Neural Network (CNN) based Gait Recognition System using Microsoft Kinect Skeleton Features
2018 ◽
Vol 7
(4.11)
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pp. 202
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Keyword(s):
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.
2021 ◽
Vol 1882
(1)
◽
pp. 012127
2021 ◽
Vol 335
(1)
◽
pp. 39-44