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 0167-8655

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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. © 2009 Elsevier B.V. All rights reserved.

Keywords:Classification performance, Embedded application, Embedded vision, Event recognition, Feature vectors, High-speed, Human-action recognition, Low dimensional, Machine learning, Motion analysis, Motion history, Motion history images, Motion information, Temporal templates, Visual motion, Image retrieval, Robot learning, Support vector machines, Gesture recognition
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
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ID Code:9915
Deposited On:16 Dec 2013 18:05

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