Citation
Kalhor, Davood and Aris, Ishak and Abdul Halin, Izhal and Moaini, Trifa
(2014)
A fast approach for human action recognition.
In: Fifth International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2014), 27-29 Jan. 2014, Langkawi, Kedah, Malaysia. (pp. 266-272).
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).
Download File
Additional Metadata
Actions (login required)
 |
View Item |
