Recurrent Neural Network for Human Action Recognition using Star Skeletonization

Authors(4) :-Anantha Prabha P, Srimathi R, Srividhya R2, Sowmiya T G

Human Action Recognition has been an active research topic since early 1980s due to its promising applications in many domains like video indexing, surveillance, gesture recognition, video retrieval and human-computer interactions where the actions in the form of videos or sensor datas are recognized. The extraction of relevant features from the video streams is the most challenging part. With the emergence of advanced artificial intelligence techniques, deep learning methods are adopted to achieve the goal. The proposed system presents a Recurrent Neural Network (RNN) methodology for Human Action Recognition using star skeleton as a representative descriptor of human posture. Star skeleton is the process of jointing the gross contour extremes of a body to its centroid. To use star skeleton as feature for action recognition, the feature is defined as a five-dimensional vector in star fashion because the head and four limbs are usually local extremes of human body. In our project, we assumed an action is composed of a series of star skeletons overtime. Therefore, images expressing human action which are time-sequential are transformed into a feature vector sequence. Then the feature vector sequence must be transformed into symbol sequence so that RNN can model the action. RNN is used because the features extracted are time dependent

Authors and Affiliations

Anantha Prabha P
Assistant Professor, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Srimathi R
UG Scholars, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Srividhya R2
UG Scholars, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Sowmiya T G
UG Scholars, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India

Human Action Recognition, Video Streams, RNN, Star skeletonization.

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Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 335-344
Manuscript Number : CSEIT195217
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Anantha Prabha P, Srimathi R, Srividhya R2, Sowmiya T G, "Recurrent Neural Network for Human Action Recognition using Star Skeletonization", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.335-344, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT195217
Journal URL : http://ijsrcseit.com/CSEIT195217

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