DocumentCode
254722
Title
Addressing System-Level Optimization with OpenVX Graphs
Author
Rainey, Erik ; Villarreal, Jesse ; Dedeoglu, Goksel ; Pulli, Kari ; Lepley, T. ; Brill, Frank
fYear
2014
fDate
23-28 June 2014
Firstpage
658
Lastpage
663
Abstract
During the performance optimization of a computer vision system, developers frequently run into platform-level inefficiencies and bottlenecks that can not be addressed by traditional methods. OpenVX is designed to address such system-level issues by means of a graph-based computation model. This approach differs from the traditional acceleration of one-off functions, and exposes optimization possibilities that might not be available or obvious with traditional computer vision libraries such as OpenCV.
Keywords
application program interfaces; computer vision; graphs; API; OpenVX graphs; computer vision libraries; computer vision system; graph-based computation model; system-level optimization; Computer vision; Digital signal processing; Graphics processing units; Kernel; Optimization; Peer-to-peer computing; Pipeline processing; OpenVX; computer vision; embedded systems; embedded vision; mobile vision; optimization; performance optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
Conference_Location
Columbus, OH
Type
conf
DOI
10.1109/CVPRW.2014.100
Filename
6910050
Link To Document