Thursday, May 25, 2017

Dynamic Vision Sensor Presenation

Toby Delbruck, University of Zurich and ETH Zurich presented "Silicon retina technology" at IEEE CAS Workshop at University of Pavia, Italy, on March 20-21, 2017. The human retina only sees motion, the behavior that was mimicked by Dynamic Vision Sensors (DVS):

10 comments:

  1. This kind of sensors are too limited in function and have very little industrial interests.

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    1. But in IoT, it is very promising.

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    2. When electricity was first publicly available it was "too limited in function" and there was "very little interest." Why dwell on the negative? Someone has invented something unique why can't you just accept that and not make pessimistic comments?

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    3. to quantify your statement of "very little industrial interests", it is about $15 million from intel in 2016. (https://venturebeat.com/2016/10/24/intel-capital-leads-15m-round-for-chronocam-to-develop-visual-sensors-for-cars-drones-and-robots/)

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    4. I don't know if it's a good idea to mention IoBS in that context :-)
      The technology is definitely interesting, but insightness still has to prove that they can do better than classical FPGA based processing approaches. The latter is definitly not geeky and power saving, but avoids a number of software problems that are way harder to solve on event based approaches of that kind.

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  2. That's interesting. What kind of IoT applications can you see please?

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  3. Just when the electricity was prseneted for the first time, it was DC. So experts were right, it was difficult to transport DC to long distance due to the resistance of wires. But what changed the scenario was the invention of AC, which can be raised and lowered in voltage. This stuff has been presented for at least 20 years and so much changes since.

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  4. Same presentation as at Electronic Imaging in February?

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  5. It was a hot research topic about 20 years ago but not until recently people found it may be useable for real applications.

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  6. The output events from this image sensor, provide the best inputs for bare-metal image processing using SNN.

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