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.
Projects
A Kaleidoscopic Approach to Surround Geometry and Reflectance Acquisition
In: CVPR Workshop on Computational Cameras and Displays (CCD), 2012
Abstract
We describe a system for acquiring reflectance fields
of objects without moving parts and without a massively
parallel hardware setup. Our system consists of a set of
planar mirrors which serve to multiply a single camera and
a single projector into a multitude of virtual counterparts.
Using this arrangement, we can acquire reflectance fields
with an average angular sampling rate of about 120+
view/light pairs per surface point. The mirror system allows
for freely programmable illumination with full directional
coverage. We employ this setup to realize a 3D acquisition
system that employs structured illumination to capture the
unknown object geometry, in addition to dense reflectance
sampling. On the software side, we combine state-of-the-art
3D reconstruction algorithms with a reflectance sharing
technique based on non-negative matrix factorization
in order to reconstruct a joint model of geometry and
reflectance. We demonstrate for a number of test scenes
that the kaleidoscopic approach can acquire complex
reflectance properties faithfully. The main limitation is
that the multiplexing approach limits the attainable spatial
resolution, trading it off for improved directional coverage.
Video Bibtex
@InProceedings{Ihrke12,
author = {Ivo Ihrke and Ilya Reshetouski and Alkhazur Manakov and Art Tevs and Michael Wand and Hans-Peter Seidel},
title = "{A Kaleidoscopic Approach to Surround Geometry and Reflectance Acquisition}",
booktitle = {Proceedings of IEEE International Workshop on Computational Cameras and Displays },
pages = "1--8",
year = {2012},
}
author = {Ivo Ihrke and Ilya Reshetouski and Alkhazur Manakov and Art Tevs and Michael Wand and Hans-Peter Seidel},
title = "{A Kaleidoscopic Approach to Surround Geometry and Reflectance Acquisition}",
booktitle = {Proceedings of IEEE International Workshop on Computational Cameras and Displays },
pages = "1--8",
year = {2012},
}