Compressive depth map acquisition using a single photon-counting detector: Parametric signal processing meets sparsity

Active range acquisition systems such as light detection and ranging (LIDAR) and time-of-flight (TOF) cameras achieve high depth resolution but suffer from poor spatial resolution. In this paper we introduce a new range acquisition architecture that does not rely on scene raster scanning as in LIDAR or on a twodimensional array of sensors as used in TOF cameras. Instead, we achieve spatial resolution through patterned sensing of the scene using a digital micromirror device (DMD) array. Our depth map reconstruction uses parametric signal modeling to recover the set of distinct depth ranges present in the scene. Then, using a convex program that exploits the sparsity of the Laplacian of the depth map, we recover the spatial content at the estimated depth ranges. In our experiments we acquired 64×64-pixel depth maps of fronto-parallel scenes at ranges up to 2.1 m using a pulsed laser, a DMD array and a single photon-counting detector. We also demonstrated imaging in the presence of unk...

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Andrea Colaco, Ahmed Kirmani, Gregory A. Howland, John C. Howell, Vivek K. Goyal
• Keywords: Computer Vision, Computer Vision Applications, Cvpr 2012, Digital Micromirror Device, Range Acquisition