Parag Beeraka, Head of the Smart Camera and Vision Business at Arm, presents the “Software-Defined Cameras for Edge Computing of the Future,” tutorial at the May 2021 Embedded Vision Summit.

Computer-vision-enabled cameras have demonstrated the potential to bring compelling functionality to numerous applications. But to realize the full potential and assist with the growth of AI-enabled cameras, it’s necessary to drastically simplify the work of developing, deploying and maintaining these cameras. Hardware and firmware standards are key to accomplishing this. In this talk, Beeraka introduces Arm’s vision for a set of hardware and software standards addressing four key elements of software-defined cameras: security, machine learning, cloud enablement and software portability.

For example, smart camera machine learning workloads can run on a variety of processing engines. Common frameworks are needed so that these workloads can be seamlessly and efficiently mapped onto the available processing engines without requiring that the camera developer delve into processing engine details. Similarly, most smart cameras are starting to rely on cloud services for storage as well as model and software updates. Standardizing interfaces to these key elements will give smart camera developers the ability to quickly integrate the cloud services best matched to their needs, without having to master the details of those elements.

See here for a PDF of the slides.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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