Real-time human action recognition on an embedded, reconfigurable video processing architecture

Abstract In recent years, automatic human action recognition has been widely researched within the computer vision and image processing communities. Here we propose a realtime, embedded vision solution for human action recognition, implemented on an FPGA-based ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human action recognition system with simple motion features and a linear support vector machine classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template class of approaches, which include ``Motion History Image'' based techniques. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfigured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemen...

• Type: Journal
• Year: 2008
• Where: JRTIP
• Authors: Hongying Meng, Michael Freeman, Nick Pears, Chris Bailey
• Keywords: Automatic Human Action, Fast Human Action, Human Action Recognition, JRTIP 2008