Embedded vision at the Edge and in the Cloud: Architectures, Algorithms, Processors, and Tools
Computer vision is rapidly becoming ubiquitous. From industrial applications like bottling lines to video cameras that can recognize people to vision-enabled home assistants that can advise you on your fashion choices, vision is showing up everywhere.
Computer vision is rapidly becoming ubiquitous. From industrial applications like bottling lines to video camerasthat can recognize people to vision-enabled home assistants that can advise you on your fashion choices, vision is showing up everywhere.
A key architectural choice underlies this ubiquity: should vision processing be done at the edge, in the cloud, or a hybrid combination of the two? In a free presentation on March 28, Jeff Bier, Founder of the Embedded Vision Alliance, will discuss the benefits and trade-offs of edge, cloud, and hybrid models, and when you should consider each option.
Within this edge-cloud framework, Jeff will also provide an update on important recent developments in the technologies enabling vision, including processors, sensors, algorithms, development tools, services and standards. Jeff will also highlight some of the most interesting and most promising end-products and applications incorporating vision capabilities.
The state-of-the-art in image acquisition and processing
Jeff Bier, Founder of the Embedded Vision Alliance, Co-Founder & President of Berkeley Design Technology, Inc.
March 28, 2018 11:00 AM EDT
Pictured: Inline FPGA processing architecture, where the camera interface is connected directly to the pins of the FPGA so the pixels are passed directly to the FPGA as they are sent from the camera.
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