Autonomous driving will be one of the major trends in the years and decades to come. Camera-based safety systems will pave the way for self-driving cars and many other innovations. Many opportunities created by these embedded vision systems can only be imagined – but they are on their way!
The potential inherent in these technologies, how long it will take until the breakthrough takes place and what is already reality today will all be discussed in a special panel discussion on the trend topic ‘Embedded Vision’, which will be organised by VDMA Machine Vision and the embedded world, the world’s leading trade fair for embedded systems.
Embedded Vision – the ‘Next Big Thing’?
Panel discussion about today’s status of embedded vision and the potentials ahead
When: 15 March 2017, 3:00 – 4:00 p.m.
Where: embedded world, NürnbergMesse, Forum in hall 3A
Participants:
- Richard York, VP Embedded Marketing, ARM Ltd.
- Arndt Bake, Chief Marketing Officer, Basler AG
- Jeff Bier, Founder, Embedded Vision Alliance, and President, BDTI
- Olaf Munkelt, Managing Director, MVTec Software GmbH
- Markus Tremmel, Driver Assistance Systems Chief Expert, Robert Bosch GmbH
- Nick Ni, Senior Product Manager, Embedded Vision and SDSoC, XILINX
‘Embedded Vision will open up new fields of application for the machine vision industry – whether it is in the factory of the future, traffic, retail, consumer products or in the medical sector. Many future visions can be realised only with embedded vision. The topic evokes great interest – among the machine vision community as well as among developers and users of embedded systems,’ says Olaf Munkelt, Chairman of the Board of VDMA Machine Vision. Benedikt Weyerer, Director Exhibitions, NürnbergMesse adds: ‘With embedded vision the embedded world will once again be introducing a topic of the future. Machine vision is an important subject and the embedded world is the right place to present it. We are looking forward to a panel discussion featuring high-calibre participants and to cooperating with VDMA Machine Vision.’
