6 accepted papers
The ability to image a scene without a direct line of sight has been demonstrated by exploiting measurements of light transients, speckle correlations, or even soft shadows (i.e., penumbra). Here, we present a new formulation of computational periscopy with an ordinary camera: a recent method that r…
We demonstrate high-quality 3D non-line-of-sight imaging by exploiting a two-edge occluder and a scene representation constructed through a Fisher information analysis. Our reconstructions are computed from a single 2D photograph, and like many computational imaging problems, this inverse problem is…
We demonstrate non-line-of-sight imaging of multi-depth scenes using only a single photograph from an ordinary digital camera. The hidden scene, comprising two images at different depths, is partially occluded from a visible wall by an opaque occluding object. The distance from the visible wall to t…
We address the problem of estimating the parameter of a Bernoulli process. This arises in many applications, including photon-efficient active imaging where each illumination period is regarded as a single Bernoulli trial. We introduce a framework within which to minimize the mean-squared error (MSE…
We present a framework for estimating non-localized sources of diffusion fields using spatiotemporal measurements of the field. Specifically in this contribution, we consider two non-localized source types: straight line and polygonal sources and assume that the induced field is monitored using a se…
In this contribution, we implement a fully distributed diffusion field estimation algorithm based on the use of average consensus schemes. We show that the field reconstruction problem is equivalent to estimating the sources of the field, and then derive an exact inversion formula for jointly recove…