Title :
Fast GPU-based space-time correlation for activity recognition in video sequences
Author :
Rofouei, Mahsan ; Moazeni, Maryam ; Sarrafzadeh, Majid
Author_Institution :
Univ. of California Los Angeles, Los Angeles, CA
Abstract :
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.
Keywords :
computer graphics; computer vision; image recognition; image sequences; video signal processing; NVIDIA Quadro FX 5600 GPU; activity recognition; computer vision; graphic processing units; space-time correlation; video browsing; video indexing; video sequences; video surveillance; Acceleration; Application software; Central Processing Unit; Computational modeling; Computer vision; Field programmable gate arrays; Graphics; Video compression; Video sequences; Video surveillance;
Conference_Titel :
Embedded Systems for Real-Time Multimedia, 2008. ESTImedia 2008. IEEE/ACM/IFIP Workshop on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-2612-6
DOI :
10.1109/ESTMED.2008.4696991
