Imaging and Computing Seminar
Vivek Goyal, Electrical Engineering and Computer Science, MIT
Title:
Compressive Depth Acquisition Cameras: Principles and Demonstrations
Abstract:
Measuring time elapsed from transmitting a pulse to receiving a reflected
response is a standard method for distance estimation. Light detection and
ranging (LIDAR) systems and time-of-flight (TOF) cameras use this principle
along with scanning by the illumination source or 2D sensor arrays to
acquire depth maps. This talk introduces depth map acquisition with high
spatial and range resolution using a single, omnidirectional, time-resolved
photodetector and no scanning components. In contrast to compressive
photography, the information of interest -- scene depths -- is nonlinearly
mixed in the measured data. The reconstruction uses parametric signal
modeling to recover a set of depths present in the scene. Then, a convex
optimization formulation that exploits sparsity of the Laplacian of the
depth map of a typical scene is used to determine correspondences between
spatial positions and depths.
We have demonstrated depth map reconstruction for both near and medium-range
scenes even in low light conditions. An initial prototype uses patterned
illumination created by a 64-by-64-pixel spatial light modulator. With this
prototype, we constructed depth maps of scenes comprising two to four planar
shapes using only 205 spatially-patterned, pulsed illuminations of the
scene. A second apparatus achieves spatially-patterned reception with a
digital micromirror device and a single photon-counting detector. With the
same mathematical framework, we constructed depth maps with and without the
presence of a partially-transmissive occluder.
Joint work with Ahmed Kirmani, Andrea Colaco, Greg Howland, John Howell, and
Franco Wong.