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Proceedings Paper

Occlusion-based computational periscopy with consumer cameras
Author(s): John Murray-Bruce; Charles Saunders; Vivek K. Goyal
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Paper Abstract

The ability to form images of scenes hidden from direct view would be advantageous in many applications – from improved motion planning and collision avoidance in autonomous navigation to enhanced danger anticipation for first-responders in search-and-rescue missions. Recent techniques for imaging around corners have mostly relied on time-of-flight measurements of light propagation, necessitating the use of expensive, specialized optical systems. In this work, we demonstrate how to form images of hidden scenes from intensity-only measurements of the light reaching a visible surface from the hidden scene. Our approach exploits the penumbra cast by an opaque occluding object onto a visible surface. Specifically, we present a physical model that relates the measured photograph to the radiosity of the hidden scene and the visibility function due to the opaque occluder. For a given scene–occluder setup, we characterize the parts of the hidden region for which the physical model is well-conditioned for inversion – i.e., the computational field of view (CFOV) of the imaging system. This concept of CFOV is further verified through the Cram´er–Rao bound of the hidden-scene estimation problem. Finally, we present a two-step computational method for recovering the occluder and the scene behind it. We demonstrate the effectiveness of the proposed method using both synthetic and experimentally measured data.

Paper Details

Date Published: 9 September 2019
PDF: 12 pages
Proc. SPIE 11138, Wavelets and Sparsity XVIII, 111380X (9 September 2019); doi: 10.1117/12.2528322
Show Author Affiliations
John Murray-Bruce, Boston Univ. (United States)
Charles Saunders, Boston Univ. (United States)
Vivek K. Goyal, Boston Univ. (United States)

Published in SPIE Proceedings Vol. 11138:
Wavelets and Sparsity XVIII
Dimitri Van De Ville; Manos Papadakis; Yue M. Lu, Editor(s)

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