Research Article | OPEN ACCESS
Multi-Features Encoding and Selecting Based on Genetic Algorithm for Human Action Recognition from Video
1Chenglong Yu, 1Xuan Wang, 2Muhammad Waqas Anwar and 1Kai Han
1Computer Application Research Center, Harbin Institute of Technology Shenzhen
Graduate School, Shenzhen, China
2Department of Computer Science, COMSATS Institute of Information Technology,
Abbottabad, Pakistan
Research Journal of Applied Sciences, Engineering and Technology 2013 21:5128-5132
Received: November 24, 2012 | Accepted: January 05, 2013 | Published: May 20, 2013
Abstract
In this study, we proposed multiple local features encoded for recognizing the human actions. The multiple local features were obtained from the simple feature description of human actions in video. The simple features are two kinds of important features, optical flow and edge, to represent the human perception for the video behavior. As the video information descriptors, optical flow and edge, which their computing speeds are very fast and their requirement of memory consumption is very low, can represent respectively the motion information and shape information. Furthermore, key local multi-features are extracted and encoded by GA in order to reduce the computational complexity of the algorithm. After then, the Multi-SVM classifier is applied to discriminate the human actions.
Keywords:
Feature encoding, feature selecting, genetic algorithm, human action recognition, multi-features,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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