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Optical Design & Engineering

Stanford distributes open-source 'Frankencamera'

Stanford University News
23 July 2010 

Stanford's open-source digital photography software platform, "Frankencamera," which allows users to create novel camera capabilities, is now available as a free download for Nokia N900 "mobile computers."

The Frankencamera engineering team will describe the platform and several sample applications created with it at next week's SIGGRAPH conference in Los Angeles.

"We're going public with Frankencamera," says Stanford computer science and electrical engineering professor Marc Levoy, who leads the project. "We are releasing code so that people can create new imaging applications on their Nokia N900s."

In addition, the researchers have been awarded a $1 million grant from the National Science Foundation, shared with colleagues at MIT, to begin making professional-style, single-lens reflex (SLR) cameras, equipped with the software platform, for free distribution to computational photography professors around the country. Non-academics could buy the camera at cost. Levoy said he expects those cameras will be available within a year.

Frankencamera began in 2006 when Levoy and Kari Pulli, a Nokia Fellow who heads a research team at Nokia Research Center Palo Alto, and a former research associate in Levoy's lab, reasoned that computational photography shouldn't be relegated to klunky research equipment in academic labs, as it has been for years. Instead it should be developed for use in the field on portable, consumer-friendly cameras.

Levoy has presented papers at several SPIE conferences, most recently at IS&T/SPIE Electronic Imaging in 2009.

The open-source camera could revolutionize digital photography. For example, it can be used to extend a camera's "dynamic range," or its ability to handle a wide range of lighting in a single frame. The process of high-dynamic-range imaging is to capture pictures of the same scene with different exposures and then to combine them into a composite image in which every pixel is optimally lit. Until now, this trick could be done only with images in computers, using photo software.