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SPECIAL REPORT: EMBEDDED VISION
Tools Move Up the Value Chain
to Take the Mystery Out of Vision AI
By Nitin Dahad
he benefits of adding vision to everyday products have EE Times ahead of the 2021 Embedded Vision Summit. While there
attracted the attention of many industries and sectors. But has been significant investment and research on the algorithms and
how do you actually get data from a camera, embed machine the silicon, the software tools that mediate between them — compil-
T learning on the device to carry out the inference algorithm, ers, optimized function libraries, and so on — have been somewhat
and enable something useful to be processed? neglected, said Bier.
The answer, as in any system design, is having the right software, Using the right software tools, compilers, and libraries can yield a
tools, libraries, compilers, and so on. It’s no surprise that such capabil- very efficient implementation of an algorithm for a particular micro-
ities are generally beyond the grasp of non-engineers. But even among controller or processor. But “over the last 30 years, semiconductor
embedded systems developers, the knowledge and skills required for companies have typically under-invested in software tools,” said Bier,
vision systems design are considered to be in short supply. a veteran of the embedded systems industry and signal processing in
One of the big challenges is lack of awareness of the software and particular. “[Software] is often viewed as a necessarily evil — it’s a cost
tools available for developing embedded-vision systems, as Jeff Bier, center in a very cost-sensitive business — and it shows. As an embed-
founder of the Edge AI and Vision Alliance, explained in a briefing with ded software developer, you might look at the tools available [to you]
Intel DevCloud for the Edge lets developers prototype computer-vision solutions in Intel’s cloud environment and watch their code run on
any combination of its available hardware resources. (Source: Intel)
JUNE 2021 | www.eetimes.eu