Micha Feigin (MIT Media Lab)
The emergence of commercial time-of-flight (ToF) cameras has
motivated extensive utilization in computer vision. Gesture recognition,
scene identification, and depth estimation are important applications that
require accurate ranging information. The current prevailing approach in ToF
uses amplitude-modulated continuous wave illumination of a scene. These ToF
cameras produce real-time range maps at a relatively low cost. However, they
are geared to measure range (or phase) for a single reflected bounce of
light and suffer from systematic errors due to multipath interference.
We show that by employing techniques such as phased diversity and custom
modulation codes and we can do such things as resolve multi path
interference, recover per pixel sparse time profiles, recover depth of
near-transparent surfaces, see through diffusers and create time-profile
movies of sweeping light.
Micha Feigin is a post doctoral researcher with the Camera Culture group at
the MIT Media lab. His current research involves utilizing super high time
resolution cameras (femto second imaging) and time of flight cameras for
looking though turbid media, acoustic tomographic imaging, radars and
Micha conducted his PhD studies under the supervision of prof. Nir Sochen
at the Tel Aviv university, where his research dealt with inverse problems,
compressed sensing and smart random sub-sampling (coresets).