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Title: Real-time human action recognition on an embedded, reconfigurable video processing architecture
Authors: Meng, H
Freeman, M
Pears, N
Bailey, C
Keywords: Embedded devices;FPGA;Computer vision;Machine learning
Issue Date: 2008
Publisher: Springer
Citation: Journal of Real-Time Image Processing, 3(3): 163 - 176, 2008
Abstract: In recent years, automatic human motion recognition has been widely researched within the computer vision and image processing communities. Here we propose a real-time embedded vision solution for human motion recognition implemented on a ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human motion recognition system with simple motion features and a linear Support Vector Machine (SVM) classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template (eg. “motion history image”) class of approaches. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfiured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemented a human motion recognition system on this reconfigurable architecture. With a small number of human actions (hand gestures), this stand-alone system is performing reliably, with an 80% average recognition rate using limited training data. This type of system has applications in security systems, man-machine communications and intelligent environments.
Description: Copyright @ 2008 Springer-Verlag.
ISSN: 1861-8200
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Research Papers

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