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The Frankencamera hardware is built from scratch using off-the-shelf components. The developers have made the details of both the hardware and software publicly available for free.

“We’ve already seen a few ideas implemented on it,” says Levoy of the Frankencamera software platform. “The one that impressed me the most was where one of our students connected two flashguns to it.” A shot of playing cards being flung into the air was captured by having one flashbulb strobe during a long exposure and the other fire brightly at the end of it. “That impressed me because he could do that in a weekend,” says Levoy.

The model used to create that image, the Frankencamera F2, is being redesigned by the Stanford team to feature an improved sensor that’s similar to the ones in professional-grade digital single-lens reflex (SLR) cameras. The F3 should be finished by the end of the year, says Levoy. A $1 million National Science Foundation grant will ensure that the camera is distributed to U.S. researchers to encourage further research, and it will also be made available for anyone to buy.

Outside of the research community, Levoy says, computational photography is most likely to make a big impact on mobile platforms. Indeed, some mobile app developers have already begun using concepts from the field, says Paul Worthington, an analyst at the San Mateo, CA, firm Future Image, which specializes in digital imaging.

An iPhone app called Pro HDR already makes it possible to take HDR images on the iPhone, although the app only combines two images. Another app, You Gotta See This, uses the gyroscope in the new iPhone 4 to create a panorama when a person scans their phone across a scene.

“Camera manufacturers used to ignore phones because they could say the image quality was too poor to worry about,” Worthington says. Now that’s changed. “Today it is smart cameras versus dumb cameras,” he says.

Levoy hopes phone vendors will adopt some of the ideas in the Frankencamera platform to enable even more powerful camera apps. But fully embracing computational photography will require more than just software tweaks to cell phones. “To really enable computational photography on smart phones, there may need to be a virtuous cycle where vendors go to their hardware suppliers and ask for more flexible components,” Levoy says.

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Credit: Stanford University
Video by Stanford

Tagged: Computing, software, photography, nokia, programming, Stanford, computational photography

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