1. [Publications](/publications) 2. Addressing System-Level Optimization with OpenVX Graphs # Addressing System-Level Optimization with OpenVX Graphs ![](/sites/default/files/styles/wide/public/pubs/2014-06_Addressing-System-Level-Optimization/Screen%20Shot%202014-05-12%20at%2010.43.13%20.png?itok=2_iq2oJP) 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. ## Authors Erik Rainey (Texas Instruments) Jesse Villareal (Texas Instruments) Goksel Dedeoglu (PercepTonic) Kari Pulli (NVIDIA) Thierry Lepley (NVIDIA) Frank Brill (NVIDIA) ## Publication Date Sunday, June 1, 2014 ## Published in [10th IEEE Embedded Vision Workshop](http://www.computervisioncentral.com/evw2014) ## Research Area [Computer Vision](/research-area/computer-vision) ## Uploaded Files [openvx\_optimization\_2014.pdf](https://research.nvidia.com/sites/default/files/pubs/2014-06_Addressing-System-Level-Optimization/openvx_optimization_2014.pdf "Open file in new window")347.66 KB ## Copyright This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to .