KEYNOTE: Event-Based Vision: A New Standard for Advanced Machine Vision Systems

Jul 21, 2022
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Sponsored by
Prophesee SA
About This Webinar
Traditional machine vison systems have relied on frame-based methods, which represent motion by capturing a number of still frames each second. For modern computer-enabled vision in industrial machines, this representation of motion is of little use. The camera is “blind” between each frame, losing information on moving objects, and each image — containing the same irrelevant background objects — is repeatedly recorded, generating excessive unhelpful data. Evolution has developed an elegant solution so that natural vision never encounters these problems. It doesn’t take frames. Cells in our eyes report back to the brain when they detect a change in the scene.

This is the founding principle behind Event-Based Vision: – Independent receptors collect all the essential information, and nothing else. Event-based vision is a paradigm-shifting advancement that uses neuromorphic techniques based on how the human eye records and interprets visual inputs. Among the benefits of the sensor technology for developers of advanced machine vision systems are energy efficiency, low latency, adaptive processing, and rapid learning. Event-based vision is ideally suited to machine vision applications — for industrial automation, IoT, automotive, and mobile cases — that require extremely-high performance, low-power operation, and/or operation in challenging lighting conditions.

***This presentation premiered during the 2022 Vision Spectra Conference. For more information on Photonics Media conferences, visit

About the presenter:
Luca VerreLuca Verre is co-founder and CEO of Prophesee, the inventor of the world’s most advanced neuromorphic vision systems. Prophesee’s patented technology is inspired by human vision, giving sight back to the blind, and unleashing new performance, safety, and autonomy standards to robots, consumer devices, and cars.

Verre is a World Economic Forum Technology Pioneer. He has extensive international management experience in the industrial and electronics sectors. Verre’s experience includes project and product management, marketing, and business development roles at Schneider Electric. Prior to Schneider Electric, he worked as a research assistant in photonics at Imperial College in London. Verre holds a Master of Science degree in physics, electronics, and industrial engineering from Politecnico di Milano and École Centrale and an MBA from INSEAD.
Sensors & Detectorsmachine visionVision Spectraevent-based vision
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