Mathematical Signal Processing Seminar: Vivek Goyal

Abstract:

LIDAR systems and time-of-flight cameras use time elapsed from transmitting a pulse and receiving a reflected response, along with scanning by the illumination source or a 2D sensor array, to acquire depth maps.  We introduce a method for compressive acquisition of scene depth with high spatial and range resolution using a single, omnidirectional, time-resolved photodetector and no scanning components.

This opens up possibilities for accurate and high-resolution 3D sensing using compact and mobile devices.

In contrast to compressive photography, the information of interest -- scene depths -- is nonlinearly mixed in the measured data.  To overcome this aspect of the inverse problem, the depth map reconstruction relies on parametric signal modeling of the impulse response of piecewise-planar scenes.  Through the use of parametric deconvolution, we achieve much finer depth resolution than dictated by the illumination pulse width and detector bandwidth alone.  Spatial resolution in our framework is rooted in patterned illumination or patterned reception followed by decoupling the inverse problems of range estimation and spatial resolution recovery during computational processing.

Our compressive depth acquisition camera (CoDAC) framework is an example of broader research themes of exploiting time resolution in optical imaging and identifying and exploiting structure in inverse problems.