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Fast GPU-based space-time correlation for activity recognition in video sequences

Mahsan Rofouei, Maryam Moazeni, Majid Sarrafzadeh
University of California Los Angeles
IEEE/ACM/IFIP Workshop on Embedded Systems for Real-Time Multimedia, 2008. ESTImedia 2008, p.33-38

@conference{rofouei2008fast,

   title={Fast GPU-based space-time correlation for activity recognition in video sequences},

   author={Rofouei, M. and Moazeni, M. and Sarrafzadeh, M.},

   booktitle={Embedded Systems for Real-Time Multimedia, 2008. ESTImedia 2008. IEEE/ACM/IFIP Workshop on},

   pages={33–38},

   year={2008},

   organization={IEEE}

}

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Action recognition is becoming an important component of many computer vision applications such as video surveillance, video indexing and browsing. However most of the space time approaches to action recognition are very computationally expensive which prevents us from using them in real-time applications. This paper describes how Graphic Processing Units (GPUs) can be used in the field of action recognition to speed up this process. We implement a space-time behavior based correlation scheme on NVIDIA Quadro FX 5600 GPU and gain a 50x speedup over its counterpart CPU implementation.
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