The big picture
This past fall, in the wide-open spaces across campus, students from Alexei Efros’s computational photography class were easy to spot—they were the ones taking camera obscura pictures with image-capturing devices made from shoeboxes. The point, says Efros, who joined the Berkeley faculty last year as an associate professor in electrical engineering and computer sciences, was for students “to become one with the photons.”
Efros is part of the Visual Computing Lab. His research combines computer graphics and computer vision to investigate larger concepts related to the visual aspects of artificial intelligence. “It’s a multidisciplinary problem connecting philosophy, neuroscience and developmental psychology.” Efros says. “It really goes to the heart of who we are.”
The Internet is awash with visual data. Given our current ability to access and process information, most of that data is inaccessible. “I hope to make visual data a first-class citizen,” says Efros. “Right now the transfer of information is tied to language. I love literature, but there is much more to the visual world. There are so many things that we just don’t have the words for.”
Using computation like cheesecloth, computer-vision researchers filter massive amounts of data into digestible nuggets of information. “To understand our visual world you need to have a lot of data,” Efros says. “You can’t understand it just with equations; you need to have the data because our world is so rich and there is so much entropy in it.”
Efros balances data-heavy computer vision research with creative computer graphics work. “You get to hack, code and play with computers. What comes out on the other end are often beautiful—sometimes bizarre, sometimes intriguing—visual representations, visual narratives even,” he says. “To me, that is very appealing aesthetically.”
Being creative while wrestling with big research questions is a priority for Efros. He once contemplated pursuing a career as a theater director. He hopes more art students will take his computational photography class in the future.
Efros’s research is also informed by his poor eyesight. “For me, this fascination for large amounts of data definitely comes from personal experience—there is this incredible power that prior experience has on what you perceive. If I have been to a place many times, then I think that I’m seeing way more than I’m actually seeing. In a familiar environment, my brain fills in the details,” he says.
“I realized how having lots of data makes all of the difference, and this is true for everyone, not just for people with poor sight.”
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