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      ComputingTopicVideoType

      Transform Your Photos with a Magic Word

      This photo editor morphs your rainy pictures into sunny days with attribute algorithms

      Sarah Lewin
      Celia Gorman
      23 Oct 2014
      Photo: Brown University
      softwaretype:videoBrown Universityalgorithmscrowdsourcingphotomachine learningBig Data

      Hate to wake up early enough to photograph the sunrise? Pierre Yves-Laffont has a solution: sleep in, take a photo later, and let a computer do the work of turning back time. He and other computer scientists at Brown University have come up with a program that can edit outdoor photographs using keywords or phrases like “more snow”, “less gloomy”, or “more daylight”.

      To build it, the researchers funneled 8500 images from over 100 outdoor webcams into a massive database, and used crowdsourcing and machine learning to teach the tool to recognize more than 40 attributes of outdoor scenes. Is it sunny? Raining? Dry? Gloomy? An algorithm identifies the differences between the same scene when viewed under various conditions by separating out the elements, such as the sky, buildings, and the ground. Each element is affected differently by an attribute change. In real life, snow is more than a simple white layer. It might make the ground white, a building darker, and the sky greyer. So the program must apply multiple changes to the user's image on a pixel level to make it look realistic.

      To use it, you simply upload a photo and enter a keyword. The algorithm can recognize the 40 attributes in any photo—not just those in the database—so it can edit most outdoor scenes.

      The photo editor can automatically change a photo to a new weather scheme, or you can use an interactive version for more control. The interactive option presents effect choices via a selection of photos that have the desired attribute in diverse ways. Then the user can specify whether they want “more snow” as in a clear winter day or "more snow" as in a blizzard.

      Researchers can now gain access to the whole dataset. According to Laffont, this is the first time an annotated database of this size has been compiled—and as more photos and variations are added, the system will become more flexible, more powerful, and better able to make dramatic changes.

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      Evan Ackerman is a senior editor at IEEE Spectrum. Since 2007, he has written over 6,000 articles on robotics and technology. He has a degree in Martian geology and is excellent at playing bagpipes.

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      Eliza Strickland is a senior editor at IEEE Spectrum, where she covers AI, biomedical engineering, and other topics. She holds a master’s degree in journalism from Columbia University.

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      dronestype:videoEast Africa dronesRwandadelivery dronesZipline360 video

      With 360 video, IEEE Spectrum takes you behind the scenes with one of the world’s first drone-delivery companies. Zipline, based in California, is using drones to deliver blood to hospitals throughout Rwanda. At an operations center in Muhanga, you’ll watch as Zipline technicians assemble the modular drones, fill their cargo holds, and launch them via catapult. You’ll see a package float down from the sky above a rural hospital, and you’ll get a closeup look at Zipline’s ingenious method for capturing returning drones.

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      www.youtube.com
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