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Title: Descriptive temporal template features for visual motion recognition
Authors: Meng, H
Pears, N
Keywords: Gesture recognition;Event recognition;Embedded vision;Motion analysis;Machine learning
Issue Date: 2009
Citation: Pattern Recognition Letters, 30(12): 1049 - 1058, 2009
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.
Description: Copyright © 2009 Elsevier B.V. All rights reserved.
ISSN: 0167-8655
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Research Papers

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