Descriptive temporal template features for visual motion recognition

Meng, Hongying and Pears, Nick (2009) Descriptive temporal template features for visual motion recognition. Pattern Recognition Letters, 30 (12). pp. 1049-1058. ISSN 1047-1160

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Descriptive temporal template features for visual motion recognition
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Full text URL: http://dx.doi.org/10.1016/j.patrec.2009.03.003

Abstract

In this paper, a human action recognition system is proposed. The system is based on new, descriptive `temporal template' features in order to achieve high-speed recognition in real-time, embedded applications. The limitations of the well known `Motion History Image' (MHI) temporal template are addressed and a new `Motion History Histogram' (MHH) feature is proposed to capture more motion information in the video. MHH not only provides rich motion information, but also remains computationally inexpensive. To further improve classification performance, we combine both MHI and MHH into a low dimensional feature vector which is processed by a support vector machine (SVM). Experimental results show that our new representation can achieve a significant improvement in the performance of human action recognition over existing comparable methods, which use 2D temporal template based representations.

Item Type:Article
Additional Information:In this paper, a human action recognition system is proposed. The system is based on new, descriptive `temporal template' features in order to achieve high-speed recognition in real-time, embedded applications. The limitations of the well known `Motion History Image' (MHI) temporal template are addressed and a new `Motion History Histogram' (MHH) feature is proposed to capture more motion information in the video. MHH not only provides rich motion information, but also remains computationally inexpensive. To further improve classification performance, we combine both MHI and MHH into a low dimensional feature vector which is processed by a support vector machine (SVM). Experimental results show that our new representation can achieve a significant improvement in the performance of human action recognition over existing comparable methods, which use 2D temporal template based representations.
Keywords:Computer vision, Image Processing, Machine Learning, Gesture recognition, Embedded vision, Motion analysis, Event recognition
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G440 Human-computer Interaction
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:1976
Deposited By:INVALID USER
Deposited On:12 Aug 2009 14:07
Last Modified:13 Mar 2013 08:33

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