ML Anthology

Addressing System-Level Optimization with OpenVX Graphs

Erik Rainey, Jesse Villarreal, Göksel Dedeoglu, Kari Pulli, Thierry Lepley, Frank Brill
CVPRW 2014 pp. 658-663
doi:10.1109/CVPRW.2014.100 /cvprw/2014/rainey2014cvprw-addressing/

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.

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Cite

Text

Rainey et al. "Addressing System-Level Optimization with OpenVX Graphs." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2014. doi:10.1109/CVPRW.2014.100

Markdown

[Rainey et al. "Addressing System-Level Optimization with OpenVX Graphs." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2014.](https://mlanthology.org/cvprw/2014/rainey2014cvprw-addressing/) doi:10.1109/CVPRW.2014.100

BibTeX

@inproceedings{rainey2014cvprw-addressing,
  title     = {{Addressing System-Level Optimization with OpenVX Graphs}},
  author    = {Rainey, Erik and Villarreal, Jesse and Dedeoglu, Göksel and Pulli, Kari and Lepley, Thierry and Brill, Frank},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2014},
  pages     = {658-663},
  doi       = {10.1109/CVPRW.2014.100},
  url       = {https://mlanthology.org/cvprw/2014/rainey2014cvprw-addressing/}
}