CODAC: Compressive Depth Acquisition Camera

Here is another compressive sensing hardware.  Vivek Goyal  does an excellent job at presenting the whole process in the following video. The attendant site is here.

The attendant papers are: CODAC: A Compressive Depth Acquisition Camera Framework by Ahmed Kirmani, Andrea Colaco, Franco N. C. Wong, and Vivek K Goyal. The abstract reads:

Light detection and ranging (LIDAR) systems use time of flight (TOF) in combination with raster scanning of the scene to form depth maps, and TOF cameras instead make TOF measurements in parallel by using an array of sensors. Here we present a framework for depth map acquisition using neither raster scanning by the illumination source nor an array of sensors. Our architecture uses a spatial light modulator (SLM) to spatially pattern a temporally-modulated light source. Then, measurements from a single omnidirectional sensor provide adequate information for depth map estimation at a resolution equal that of the SLM. Proof-of-concept experiments have verified the validity of our modeling and algorithms.

Also

Exploiting sparsity in time-of-flight range acquisition using a single time-resolved sensor by by Ahmed Kirmani, Andrea Colaco, Franco N. C. Wong, and Vivek K Goyal. The abstract reads:

Range acquisition systems such as light detection and ranging (LIDAR) and time-of-flight (TOF) cameras operate by measuring the time difference of arrival between a transmitted pulse and the scene reflection. We introduce the design of a range acquisition system for acquiring depth maps of piecewise-planar scenes with high spatial resolution using a single, omnidirectional, time-resolved photodetector and no scanning components. In our experiment, we reconstructed 64 × 64-pixel depth maps of scenes comprising two to four planar shapes using only 205 spatially-patterned, femtosecond illuminations of the scene. The reconstruction uses parametric signal modeling to recover a set of depths present in the scene. Then, a convex optimization that exploits sparsity of the Laplacian of the depth map of a typical scene determines correspondences between spatial positions and depths. In contrast with 2D laser scanning used in LIDAR systems and low-resolution 2D sensor arrays used in TOF cameras, our experiment demonstrates that it is possible to build a non-scanning range acquisition system with high spatial resolution using only a standard, low-cost photodetector and a spatial light modulator

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