Title :
Recognizing heuman actions based on motion information and SVM
Author :
Meng, Hongying ; Pears, Nick ; Bailey, Chris
Author_Institution :
Dept. of Comput. Sci., York Univ.
Abstract :
In this paper, we propose a new system for human action recognition with a view to applications in security systems, man-machine communications and intelligent environments. Our system is based on very simple features in order to achieve high-speed recognition in real-world applications. We have chosen three main techniques to build a system that can work in real-time. Firstly, we choose motion history images and related features. Secondly, we use a template matching methods instead of state-space methods that need expensive modelling processes; finally, we use linear classifier support vector machine (SVM) for fast classification. Experimental results show that this system can achieve good performance in human action recognition in realtime embedded applications, such as intelligent environments
Keywords :
gesture recognition; image classification; image matching; image motion analysis; support vector machines; human action recognition; intelligent environments; linear classifier SVM; man-machine communications; motion history images; motion information; security systems; support vector machine; template matching methods;
Conference_Titel :
Intelligent Environments, 2006. IE 06. 2nd IET International Conference on
Conference_Location :
Athens
Print_ISBN :
978-0-86341-663-7