A team of researchers from Cambridge University is borrow some of the techniques used in autonomous vehicles to instruct your phone to pilot , even when it does n’t have access to position information like a GPS signal .

In fact , the team has developed two new pieces of software that track down on peregrine phone but reckon a little like driverless cars . The first , called SegNet , can take footage of a street scene from a smartphone ’s television camera and classify it , sort object into 12 dissimilar family – such as road , street sign , walker , edifice and cyclists . you may see it in action mechanism above . The team explain how it work :

SegNet learns by example – it was ‘ coach ’ by an industrious group of Cambridge undergraduate scholarly person , who manually labelled every pixel in each of 5000 images , with each picture taking about 30 minutes to complete . Once the labelling was finished , the researchers then took two days to ‘ train ’ the system of rules before it was put into action .

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The team claim “ it can deal with unclouded , shadow and nighttime - time environments , and currently labels more than 90 % of pixels aright . ”

The second organisation uses footage from the street vista to discern where the telephone set is , using the geometry of building and street furniture to distinguish position . The organization has so far been prove in the center of Cambridge , where it ’s been shown to be “ far more accurate than GPS . ” It ’s very similar to the way most autonomous cars , including those made by Google , liken sensed data to existing prior mapsto East themselves on the road .

Do n’t opine that your earpiece will suddenly turn your car into an self-reliant vehicle , though . “ In the short term , we ’re more likely to see this sorting of system on a domestic golem – such as a robotlike vacuum cleanser , for instance , ” explain Roberto Cipolla , one of the researchers working on the task , in a pressure release . begin ta set forth somewhere , eh ?

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[ Cambridge University ]

Autonomous CarsMobile phoneTechnology

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