DocumentCode :
3661592
Title :
A Fast Approach for Human Action Recognition
Author :
Davood Kalhor;Ishak Aris;Izhal Abdul Halin;Trifa Moaini
Author_Institution :
Dept. of Electr. &
fYear :
2014
Firstpage :
266
Lastpage :
272
Abstract :
This paper presents a fast approach to represent and recognize human actions. For representation, a feature vector is constructed from spatiotemporal data of silhouettes based on appearance and motion. For classification, a new Radial Basis Function Network (RBF), called Time Delay Input Radial Basis Function Network is proposed by introducing time delay units to the RBF in a novel approach. The proposed network has a few desirable features such as easier learning process and more flexibility. The representational power and speed of the proposed method for action recognition were evaluated using a publicly available dataset. Based on experimental results, implemented in MATLAB and on standard PCs, the average time for constructing a feature vector for a high-resolution video is almost 20 ms/frame. Furthermore, the proposed approach demonstrates good performance in terms of execution time and overall performance (a new performance measure that combines accuracy and speed into one metric).
Keywords :
"Training","Feature extraction","Accuracy","Prototypes","Shape","Delay effects","Real-time systems"
Publisher :
ieee
Conference_Titel :
Intelligent Systems, Modelling and Simulation (ISMS), 2014 5th International Conference on
ISSN :
2166-0662
Type :
conf
DOI :
10.1109/ISMS.2014.52
Filename :
7280919
Link To Document :
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