There is a World Between Frames: Event Cameras Come of Age for Machine Vision in Industrial Automation
Originally Recorded May 12, 2022 | 11 AM - NOON ET
ABOUT THIS WEBINAR
From predictive maintenance to high-speed counting, to process monitoring and inspection, seeing all the details is critical. Traditional frame-based machine vision systems have inherent limitations in providing a complete picture. And, given the demands of today’s complex vision system requirements, frame-based cameras face significant challenges, such as generating too much data, being subject to motion blur, reacting and operating too slowly, too expensive and complex to set up and having low dynamic range.
A new breed of event cameras, using neuromorphic methods that mimic the human eye and brain, address these challenges with an approach that provides an uninterrupted stream for continuous and comprehensive monitoring. The sensors in these cameras feature pixels, each powered by their own embedded intelligent processing, allowing them to activate independently every time something changes in a scene – an event. This vision sensing technology delivers unprecedented speed (>10 000 fps time resolution equivalent), dynamic range (>120dB), data volume (10x to 1000x less) and power efficiency (<10 mW). Event-Based Metavision can be easily integrated into machine vision systems for any kind of operating environment, achieves ultra-high speed and ultra-slow-motion, and works in even the most challenging lighting conditions.
This webinar will show how event cameras are bringing new levels of performance and efficiency to safety, reliability efficiency and user experiences across a broad range of applications, such as high-speed counting, smart detection and tracking, vibration monitoring, Spatter Monitoring, Machine Learning, ultra-slow motion, optical flow, kinematic monitoring and many more.
- Learn what event-based vision is, and its inherent advantages
- Understand how Event-Based Metavision can be applied to achieve new performance and efficiency levels in inspection, counting, predictive maintenance and monitoring
- Explore specific use case examples that demonstrate the power and flexibility of Event-Based Metavision
- Learn about the growing ecosystem of development support available for event cameras.
The company developed a breakthrough Event-Based Vision approach to machine vision. This new vision category allows for significant reductions of power, latency and data processing requirements to reveal what was invisible to traditional frame-based sensors until now. Prophesee’s patented Metavision® sensors and algorithms mimic how the human eye and brain work to dramatically improve efficiency in areas such as autonomous vehicles, industrial automation, IoT, security and surveillance, and AR/VR.
Prophesee is based in Paris, with local offices in Grenoble, Shanghai, Tokyo and Silicon Valley. The company is driven by a team of more than 100 visionary engineers, holds more than 50 international patents and is backed by leading international investors including Sony, iBionext, 360 Capital Partners, Intel Capital, Robert Bosch Venture Capital, Supernova Invest, and European Investment Bank. More information can be found at www.prophesee.ai.
Luca Verre, CEO and Co-FounderLuca 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 safety standards and autonomy to cars, robots and mobile devices.
Luca is a World Economic Forum Technology Pioneer. He has extensive international management experience in the industrial and electronics sectors. His experience includes project and product management, marketing and business development roles at Schneider Electric. Prior to Schneider Electric, Luca worked as a Research Assistant in Photonics at the Imperial College of London. Luca holds a MSc in Physics, Electronic and Industrial Engineering from Politecnico di Milano and Ecole Centrale and an MBA from INSEAD.
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