Paper Info
Title
Fast GPU-based space-time correlation for activity recognition in video sequences
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.
Year
DOI
Venue
2008
10.1109/ESTMED.2008.4696991
Atlanta, GA
Keywords
Field
DocType
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
Video browsing,Graphics,Computer vision,Activity recognition,Computer science,CUDA,Search engine indexing,Image processing,Video tracking,Artificial intelligence,Speedup
Conference
ISBN
Citations 
PageRank 
978-1-4244-2612-6
4
0.68
References 
Authors
7
3
Name
Order
Citations
PageRank
Mahsan Rofouei1889.58
Maryam Moazeni2403.81
Majid Sarrafzadeh33103317.63