Generalized Image Acquisition and Analysis

On Plenoptic Multiplexing and Reconstruction

Photography has been striving to capture an ever increasing amount of visual information in a single image. Digital sensors, however, are limited to recording a small subset of the desired information at each pixel. A common approach to overcoming the limitations of sensing hardware is the optical multiplexing of high-dimensional data into a photograph. While this is a well-studied topic for imaging with color filter arrays, we develop a mathematical framework that generalizes multiplexed imaging to all dimensions of the plenoptic function. This framework unifies a wide variety of existing approaches to analyze and reconstruct multiplexed data in either the spatial or the frequency domain. We demonstrate many practical applications of our framework including high-quality light field reconstruction, the first comparative noise analysis of light field attenuation masks, and an analysis of aliasing in multiplexing applications.


Discovering the Structure of a Planar Mirror System from Multiple Observations of a Single Point

Ilya Reshetouski, Alkhazur Manakov, Ayush Bhandari, Ramesh Raskar, Hans-Peter Seidel, Ivo Ihrke
CVPR 2013


We investigate the problem of identifying the position of a viewer inside a room of planar mirrors with unknown geometry in conjunction with the room’s shape parameters. We consider the observations to consist of angularly resolved depth measurements of a single scene point that is being observed via many multi-bounce interactions with the specular room geometry. Applications of this problem statement include areas such as calibration, acoustic echo cancelation and time-of-flight imaging. We theoretically analyze the problem and derive sufficient conditions for a combination of convex room geometry, observer, and scene point to be reconstructable. The resulting constructive algorithm is exponential in nature and, therefore, not directly applicable to practical scenarios. To counter the situation, we propose theoretically devised geo- metric constraints that enable an efficient pruning of the solution space and develop a heuristic randomized search algorithm that uses these constraints to obtain an effective solution. We demon- strate the effectiveness of our algorithm on extensive simulations as well as in a challenging real-world calibration scenario.


author = {Ilya Rehsetouski and Alkhazur Manakov and Ayush Bhandari and Ramesh Raskar and Hans-Peter Seidel and Ivo Ihrke},
title = {Discovering the Structure of a Planar Mirror System from Multiple Observations of a Single Point},
booktitle = {Proceedings of CVPR},
year = 2013,
pages = {xx--yy},
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