Computing Power Becoming More Human Like

— June 13, 2014

Twenty leading computer vision and imaging scientists from Xerox will join their peers from Google, Facebook, Microsoft Research, Amazon and many of the world’s top academic institutions later this month at a conference, to share their research on making computers more “human like,” mimicking how the brain sees and thinks.
 
The annual IEEE Computer Vision/Pattern Recognition Conference draws top global scientists who work on ways to advance computer vision, a field that empowers machines to “see” and make sense of the world, augmenting and often exceeding human capabilities.
 
“Xerox has firsthand knowledge of business processes across many industries, and is a pioneer in teaching computers to extract meaningful and actionable analytics from images and video,” said Raja Bala, a Xerox principal scientist in Webster, N.Y. “Although there’s been significant progress in recent years, a number of scientific challenges remain to be resolved.”
 
Xerox research to be presented includes:
 
Detecting cell phone use by highway drivers: Motivated by its impact on public safety and property, several state and federal government organizations prohibit cell phone use while driving. Xerox scientists are working on a camera system for highways that uses pattern recognition technology to detect if a driver is using a cell phone.
 
Turning smartphones into a personal driving coach: Researchers in Webster are also working on a computer vision project that would turn smartphones into driving assistants. Using facial feature detection technology, the phone estimates a driver’s gaze direction, and detects if a driver is distracted and not paying attention to the road.
 
Making images more eye catching: Researchers from both Xerox in Europe and at Harvard University are studying what attracts people’s attention first when they look at a picture. Understanding that eye-catching element enables visuals to be composed for greater effect and can predict where people will look when facing a scene, a photo or game.
 
Making sense of big data in computer vision – image signatures: Images and video make up 90% of today’s Internet traffic. To explore and use this massive amount of data requires technology that can automatically analyze an image and create a unique  visual signature  that distinguishes it from other images. The Xerox Research Centre Europe (XRCE) has invented a patented methodology that creates such signatures in an extremely compact and robust fashion, beating current, deep learning methods for such challenging image classification problems as recognizing the brand and model of a car.
 
Pigeon or dove? Designing ‘gold’ questions in complex crowdsourcing tasks: Crowdsourcing is frequently used as a forum to find individuals to label images but presents challenges when specific subject matter experts are required (such as ornithologists to identify species of birds), since such experts are rarely available on crowdsourcing platforms.
 
To assist non-expert annotators, the Xerox research centers in Europe and India have designed a system that can do a first filter to propose a very limited number of categories to choose from. The system automatically includes ‘gold’ questions to identify untrustworthy annotators and ensure the quality of labeling.
 
Xerox conducts computer vision research at its centers in New York and France. The Xerox Innovation Group also collaborates with the world’s top academic institutions including the University of Oxford, Harvard University, the French National Institute for Research in Computer Science (INRIA), the Massachusetts Institute of Technology, Carnegie Mellon, the University of Illinois at Urbana-Champaign, Penn State University, Notre Dame and University of Maryland.

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