Fujitsu is getting the real and virtual world a bit closer together

April 18, 2013

Fujitsu Laboratories has developed a technology that can overlay an interactive touchscreen over real-world objects, such as paper.

This would mean an easier handling of non digital data like books.

fujitsu-touchscreen-interface-for-paper-650x0

Using a low-resolution webcam (just 320 x 180 pixel resolution) and a commercial projector, the Japanese company is able to project an interface onto a surface, and then use the camera to track both the shape of the item as well as your fingers to determine what to do. For example, in the video demo from DigInfoNews, the Fujitsu rep is able to digitally crop out just the photo on the printed piece of paper by sliding the sheet under the device, and using only his finger to manipulate the interface projected onto the paper.

Fujitsu said:

“We think paper and many other objects could be manipulated by touching them, as with a touchscreen. This system doesn’t use any special hardware; it consists of just a device like an ordinary webcam, plus a commercial projector. Its capabilities are achieved by image processing technology.”

Besides flat surfaces, the technology also works on curved or uneven ones, so one can easily manipulate data from a book.

The fully commercial version of the technology will be ready for release in 2014.

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Mercedes-Benz needs Big Data solutions to be ahead in connected car technologies

April 17, 2013

Mercedes-Benz, Bosch and HDI have partnered up with European accelerator network Startupbootcamp to access ideas in the fields of connectivity, mobility and big data.

As part of this partnership, called SBC2go, the partners will provide financial resources, mentors and marketing support to startups selected to participate in the programme.

Dr. Frank Spennemann from Daimler lab and Mercedes-Benz says partnering with Startupbootcamp Berlin will “accelerate our access to innovation and will plug us into an impressive community of alumni, mentors and investors. At the same time we support start-ups in developing business ideas and increase their market value. Due to our global presence we can open doors to new markets.”

So, what is Mercedes-Benz, Bosh and HDI looking for?

E.g. Daimler has a number of initiatives already such as the Car2Go car-sharing service which has over 7,000 vehicles in 18 cities on the road in Europe and North America

They need basic, advanced and realtime data anlytics. How basic traffic data analytics can look like, can already be seen at  uber.com

uber - networks, showing probabilities

Here are San Francisco’s location networks, showing the probability that a ride starts in one neighborhood and ends in another.

Having this kind of analytics in realtime, car sharing service car2go could offer e.g. dynamic pricing. This would mean an competitve advantge to DriveNow (BMW), flinkster (Deutsche Bahn) and ZebraMobil.

It is great to see that Mercedes-Benz, Bosch and HDI are supporting the Berlin start-up ecosystem. The output of this partnership will be definitely interesting.

Links:

http://www.startupbootcamp.org/blog/the-big-league-startupbootcamp-berlin-partners-up-with-mercedes-benz-hdi-and-bosch-for-sbc2go.html

http://techcrunch.com/2013/04/16/mercedes-benz-bosch-and-hdi-create-new-accelerator-with-startupbootcamp-berlin/

http://blog.uber.com/2012/01/09/uberdata-san-franciscomics/

 

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Tim O’Reilly on Humans, Machines and Data at Stanford

March 12, 2013

Tim O’Reilly uses examples from Google’s autonomous Vehicle project to highlight the developing changes and interactions in the relationship between humans, machines and data (human-machine symbiosis).

How can it be that during the  DARPA Grand Challenge an autonomous car drove 7 miles in 7 hours and 6 years later Google autonomous Vehicle drove 100 000 miles?

Peter  Norvig, Chief Scientist, of Google has an explanation: “We  don’t have  better  algorithms. We just have  more  data.”
The data was the Google street-view vehicle. The data came from humans who drove with the Google street-view cars the roads, equipped with detailed sensors which measured, photographed and collected all the data. The data was stored in the cloud and made available to the Google autonomous Vehicle. This is an example for rethinking human-machine symbiosis.

All this data makes the Google autonomous Vehicle project just possible. It is a fairly hard AI problem to pic a traffic light out of a video stream. It is a trivial AI problem to figure out if it is red or green if you already know it is there.

Read more: e-corner Stanford University’s Entrepreneurship Corner
Stanford Technology Ventures Program (March 6, 2013)

 

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