scholarly journals AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos

2017 ◽  
Author(s):  
Amlan Kar ◽  
Nishant Rai ◽  
Karan Sikka ◽  
Gaurav Sharma
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Deep Convolutional Neural Networks

scholarly journals Human action recognition using support vector machines and 3D convolutional neural networks

2017 ◽  
Vol 3 (1) ◽  
pp. 47 ◽  
Author(s):  
Majd Latah
Keyword(s):  
Neural Networks ◽  
Support Vector Machines ◽  
Convolutional Neural Networks ◽  
Action Recognition ◽  
Recognition Task ◽  
Human Action Recognition ◽  
Human Action ◽  
Support Vector ◽  
Deep Convolutional Neural Networks ◽  
Vector Machines

Recently, deep learning approach has been used widely in order to enhance the recognition accuracy with different application areas. In this paper, both of deep convolutional neural networks (CNN) and support vector machines approach were employed in human action recognition task. Firstly, 3D CNN approach was used to extract spatial and temporal features from adjacent video frames. Then, support vector machines approach was used in order to classify each instance based on previously extracted features. Both of the number of CNN layers and the resolution of the input frames were reduced to meet the limited memory constraints. The proposed architecture was trained and evaluated on KTH action recognition dataset and achieved a good performance.

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