E-Book, Englisch, 372 Seiten
Brill / Erukhimov / Giduthuri OpenVX Programming Guide
1. Auflage 2020
ISBN: 978-0-12-816619-2
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark
E-Book, Englisch, 372 Seiten
ISBN: 978-0-12-816619-2
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark
OpenVX is the computer vision API adopted by many high-performance processor vendors. It is quickly becoming the preferred way to write fast and power-efficient code on embedded systems. OpenVX Programming Guidebook presents definitive information on OpenVX 1.2 and 1.3, the Neural Network, and other extensions as well as the OpenVX Safety Critical standard. This book gives a high-level overview of the OpenVX standard, its design principles, and overall structure. It covers computer vision functions and the graph API, providing examples of usage for the majority of the functions. It is intended both for the first-time user of OpenVX and as a reference for experienced OpenVX developers. - Get to grips with the OpenVX standard and gain insight why various options were chosen - Start developing efficient OpenVX code instantly - Understand design principles and use them to create robust code - Develop consumer and industrial products that use computer vision to understand and interact with the real world
Frank Brill manages OpenVX software development for Cadence's Tensilica Imaging and Vision DSP organization. Frank obtained his PhD in Computer Science from the University of Virginia and started his career doing computer vision research and development for video security and surveillance applications at Texas Instruments, where he obtained 5 patents related to this work. He then moved into silicon device program management, where he was responsible for several digital still camera and multimedia chips, including the first device in TI's DaVinci line of multimedia processors (the DM6446). Frank worked at NVIDIA from 2013 to 2014, where he managed the initial development of NVIDIA OpenVX-based VisionWorks toolkit, and then worked at Samsung from 2014 to 2016, where he managed a computer vision R&D team in Samsung Mobile Processor Innovation Lab.
