ICTACT Journal on Image and Video Processing

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Robust Method or Human Action Recognition in Video Streams Using Skeleton Graph based CNN


Affiliations
1 Department of Computer Science and Engineering, KVG College of Engineering, India
2 Department of Information Science, NITTE University, India
     

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Understanding the action of human plays an important role in public gatherings and recognition of human action is a major problem which leads to analysis the human activities. In many years, people are interested for detecting the human activity. Human behavior analysis are used in many areas like video surveillance, banks to increase public security. To detect the human behavior from the videos, essential features are to be detected. The major challenge in human action recognition is to generate the required features significance changes occurred in human action. Nowadays skeleton data-based action detection becoming more popular. In order to counterpart such limitations, this paper brings a method using Skeleton Graph based deep learning convolutional neural network. The proposed method gives accuracy of 0.93.

Keywords

Human Action Recognition, Skeletization, Convolutional Neural Network, Skeleton Graph
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  • Robust Method or Human Action Recognition in Video Streams Using Skeleton Graph based CNN

Abstract Views: 150  |  PDF Views: 2

Authors

K.L. Bhagya Jyothi
Department of Computer Science and Engineering, KVG College of Engineering, India
Vasudeva
Department of Information Science, NITTE University, India

Abstract


Understanding the action of human plays an important role in public gatherings and recognition of human action is a major problem which leads to analysis the human activities. In many years, people are interested for detecting the human activity. Human behavior analysis are used in many areas like video surveillance, banks to increase public security. To detect the human behavior from the videos, essential features are to be detected. The major challenge in human action recognition is to generate the required features significance changes occurred in human action. Nowadays skeleton data-based action detection becoming more popular. In order to counterpart such limitations, this paper brings a method using Skeleton Graph based deep learning convolutional neural network. The proposed method gives accuracy of 0.93.

Keywords


Human Action Recognition, Skeletization, Convolutional Neural Network, Skeleton Graph

References