David Lindell, a graduate student in electrical engineering at Stanford University, donned a high visibility tracksuit and got to work, stretching, pacing and hopping across an empty room.
David Lindell, a graduate student in electrical engineering at Stanford University, donned a high visibility tracksuit and got to work, stretching, pacing and hopping across an empty room. Through a camera aimed away from Lindell – at what appeared to be a blank wall – his colleagues could watch his every move.
That’s because, hidden to the naked eye, he was being scanned by a high powered laser and the single particles of light he reflected onto the walls around him were captured and reconstructed by the camera’s advanced sensors and processing algorithm.
“People talk about building a camera that can see as well as humans for applications such as autonomous cars and robots, but we want to build systems that go well beyond that,” said Gordon Wetzstein, an assistant professor of electrical engineering at Stanford. “We want to see things in 3D, around corners and beyond the visible light spectrum.”
The camera system Lindell tested, which the researchers are presenting at the SIGGRAPH 2019 conference Aug. 1, builds upon previous around-the-corner cameras this team developed. It’s able to capture more light from a greater variety of surfaces, see wider and farther away and is fast enough to monitor out-of-sight movement – such as Lindell’s calisthenics – for the first time. Someday, the researchers hope superhuman vision systems could help autonomous cars and robots operate even more safely than they would with human guidance.
Read more at Stanford University
