Analyzing Depth from Coded Aperture Sets

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Analyzing Depth from Coded Aperture Sets
Computational depth estimation is a central task in computer vision and graphics. A large variety of strategies have been introduced in the past relying on viewpoint variations, defocus changes and general aperture codes. However, the tradeoffs between such designs are not well understood. Depth estimation from computational camera measurements is a highly non-linear process and therefore most research attempts to evaluate depth estimation strategies rely on numerical simulations. Previous attempts to design computational cameras with good depth discrimination optimized highly non-linear and non-convex scores, and hence it is not clear if the constructed designs are optimal. In this paper we address the problem of depth discrimination from J images captured using J arbitrary codes placed within one fixed lens aperture. We analyze the desired properties of discriminative codes under a geometric optics model and propose an upper bound on the best possible discrimination. We show that un...
Added 27 Jul 2010
Updated 27 Jul 2010
Type Conference
Year 2010
Where ECCV
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