On Twitter, Laurent reminded me of this excellent paper using Kaleidoscopes to produce a multi-view of a scene in Three-Dimensional Kaleidoscopic Imaging by Ilya Reshetouski, Alkhazur Manakov, Hans-Peter Seidel, and Ivo Ihrke.
Surely this is an instance of compressive sensing but it doesn't seem like the authors have looked into compressive reconstruction solvers to get back images. One of the reason is the time they spend in the calibration of this camera. This brought me back to this question on the LinkedIn Group:
What about hardware implementations of CS? Is TI's DMD the only solution for building a real "single-pixel" camera. Are there any interesting hardware implementations of CS?
And the answer is yes there are other interesting hardware implementation even if sometimes, people do not use the words compressive imaging. The earliest instance I can think of, besides coded aperture, is the random lens imager but other instances exist such as this optically multiplexed imaging [2,3] system. Eventually, one wonders if parts of the calibration process could not come easier if it were to use some sort of dynamic scene and structured sparsity approach such as featured in How many lightbulbs does it take to locate somebody ?
 Three-Dimensional Kaleidoscopic Imaging by Ilya Reshetouski, Alkhazur Manakov, Hans-Peter Seidel, and Ivo Ihrke: Paper [pdf], Supplemental materials [pdf], Presentation [ppt]
 Optically multiplexed imaging with superposition space tracking by Shikhar Uttam, Nathan A.Goodman,Mark A. Neifeld, Changsoon Kim, Renu John, Jungsang Kim, and David Brady.
 Fast disambiguation of superimposed images for increased field of view by Roummel Marcia, Changsoon Kim, Jungsang Kim, David Brady, and Rebecca Willett
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