A ROBUST METHOD FOR HUMAN ACTION RECOGNITION IN VIDEO STREAMS USING SKELETON GRAPH BASED CNN

ICTACT Journal on Image and Video Processing ( Volume: 12 , Issue: 4 )

Abstract

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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.

Authors

K.L. Bhagya Jyothi1, Vasudeva2
KVG College of Engineering, India1, NITTE University, India2

Keywords

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

Published By
ICTACT
Published In
ICTACT Journal on Image and Video Processing
( Volume: 12 , Issue: 4 )
Date of Publication
May 2022
Pages
2693-2698
Page Views
360
Full Text Views
5

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