אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

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.

Bio:
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 compressed sensing.

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).