Paper Info
Title
Efficient design and implementation of visual computing algorithms on the GPU
Abstract
In this paper, we explore the key factors in the design and implementation of visual computing (image processing and computer vision) algorithms on the massive parallel GPU (graphics processing units). The goal of the exploration is to provide common perspective and guidelines of using GPU for visual computing applications. We have selected three nontrivial applications (multiview stereo matching, linear feature extraction, and JPEG2000 image encoding) for the benchmarks, which show different characteristics in GPU parallel computing. Intensive analysis is performed to evaluate the characteristic of each algorithm and its effect on the performance. Based on this, we draw general guidelines of using GPU for the visual computing algorithms.
Year
DOI
Venue
2009
10.1109/ICIP.2009.5414207
ICIP
Keywords
Field
DocType
efficient design,image coding,image matching,image processing,gpu,computer vision algorithms,gpu parallel computing,multiview stereo matching,graphics processing units,computer graphics,data compression,jpeg2000 image encoding,visual computing,visual computing algorithms,common perspective,feature extraction,different characteristic,computer vision,linear feature extraction,gpgpu,coprocessors,visual computing algorithm,parallel computing,stereo image processing,massive parallel gpu,visual computing application,visualization,kernel,algorithm design and analysis,parallel computer,transform coding,pixel
Graphics,Visual computing,Computer vision,CUDA,Computer science,Algorithm,Image processing,Feature extraction,Artificial intelligence,General-purpose computing on graphics processing units,Coprocessor,Computer graphics
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-5655-0
978-1-4244-5655-0
4
PageRank 
References 
Authors
0.61
5
4
Name
Order
Citations
PageRank
In Kyu Park131635.97
Nitin Singhal211310.55
Man Hee Lee3778.18
Sungdae Cho417715.35