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

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5 Author(s)
Colaco, A. ; Massachusetts Inst. of Technol., Cambridge, MA, USA ; Kirmani, A. ; Howland, G.A. ; Howell, J.C.
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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 two-dimensional 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 unknown partially-transmissive occluders. The prototype and results provide promising directions for non-scanning, low-complexity range acquisition devices for various computer vision applications.

Published in:

Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on

Date of Conference:

16-21 June 2012