Addressing System-Level Optimization with OpenVX Graphs

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)

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