Join us at the Embedded Vision Summit 2023, the premier conference for innovators incorporating computer vision and edge AI in products in Santa Clara, CA, May 22nd through May 24th!  As a proud sponsor, The Khronos Group will be sharing the latest on our advanced, royalty-free interoperability standards for embedded vision processing and Machine Learning.  Visit us at booth #1140 for live demos!

 

Khronos Booth at the Embedded Vision Summit

• Location: Santa Clara Convention Center, Booth #1140
• Tuesday, May 23: 12:00 - 17:30
• Wednesday, May 24: 10:00 - 18:00

Khronos Related Presentations

Open Standards Unleash Hardware Acceleration for Embedded Vision

• Date: Tuesday, May 23
• Time: 14:05 - 14:35 | EVS Session Description
• Speaker: Neil Trevett - President, The Khronos Group
• Abstract: Offloading visual processing to a hardware accelerator has many advantages for embedded vision systems. Decoupling hardware and software removes barriers to innovation and shortens time to market. Using hardware acceleration, embedded vision system manufacturers can integrate and deploy new components more easily, provide cross-generation reusability and facilitate field upgradability. Embedded system hardware acceleration is made possible by open standards for acceleration and interfacing, which reduce costs and lower the barriers to advanced techniques such as inferencing and vision acceleration. In this session, Neil Trevett, Khronos Group President, will explain how hardware accelerators can help offload vision processing and inferencing to speed development. Neil will give an overview of the Khronos Group family of open standards for programming and deploying accelerated inferencing and embedded vision and share the latest progress from the Kamaros API Working Group, which is dedicated to the development of an open-standard camera system API.

The OpenVX Standard API: Computer Vision for the Masses

• Date: Wednesday, May 24
• Time: 14:40 - 15:10 | EVS Session Description
• Speaker: Kiriti Nagesh-Gowda - SMTS Engineer, AMD; OpenVX Working Group Chair
• Abstract: Today, a great deal of effort is wasted in optimizing and re-optimizing computer vision and machine learning application software as algorithms change and as developers target different processors. Developers need a way to deploy their applications on any processor, taking advantage of processor features that boost performance without having to worry about the details of mapping each algorithm to each processor. OpenVX is a mature, open and royalty-free standard for cross-platform acceleration. It enables computer vision and machine learning applications to be written once, and then run on a variety of target processors, taking advantage of each processor’s unique capabilities. In this talk, we’ll explore the key features of OpenVX 1.3.1 and show how developers are leveraging them. We will illustrate the performance, portability and memory footprint advantages of OpenVX via open-source code samples. We will also share new OpenVX extensions and usability enhancements.