vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff9e612c00000040dc0e0001000100 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.
K.L. Bhagya Jyothi1, Vasudeva2
KVG College of Engineering, India1, NITTE University, India2
Human Action Recognition, Skeletization, Convolutional Neural Network, Skeleton Graph
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 12 , Issue: 4 , Pages: 2693-2698 )
Date of Publication :
May 2022
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