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Addressing System-Level Optimization with OpenVX Graphs
AbstractDuring 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.
Related Material
[pdf][bibtex]@InProceedings{Rainey_2014_CVPR_Workshops,
author = {Rainey, Erik and Villarreal, Jesse and Dedeoglu, Goksel and Pulli, Kari and Lepley, Thierry and Brill, Frank},
title = {Addressing System-Level Optimization with OpenVX Graphs},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2014}
}
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