Generalized Image Acquisition and Analysis
Computational Plenoptic Imaging
The plenoptic function is a ray-based model for light that includes the color spectrum as well as spatial,
temporal, and directional variation. Although digital light sensors have greatly evolved in the last years,
one fundamental limitation remains: all standard CCD and CMOS sensors integrate over the dimensions of the
plenoptic function as they convert photons into electrons; in the process, all visual information is irreversibly
lost, except for a two-dimensional, spatially-varying subset - the common photograph. In this state of the
art report, we review approaches that optically encode the dimensions of the plenpotic function transcending
those captured by traditional photography and reconstruct the recorded information computationally.
Projects
Three-Dimensional Kaleidoscopic Imaging
In: Proceedings of CVPR 2011 (oral).
Abstract
Three-dimensional kaleidoscopic imaging, a promising alternative for recording multi-view imagery. The main limitation of multi-view reconstruction techniques is the limited number of views that are available from multi-camera systems, especially for dynamic scenes. Our new system is based on imaging an object inside a kaleidoscopic mirror system. We show that this approach can generate a large number of high-quality views well distributed over the hemisphere surrounding the object in a single shot. In comparison to existing multi-view systems, our method offers a number of advantages: it is possible to operate with a single camera, the individual views are perfectly synchronized, and they have the same radiometric and colorimetric properties. We describe the setup both theoretically, and provide methods for a practical implementation. Enabling interfacing to standard multi-view algorithms for further processing is an important goal of our techniques.
Project Page Slides Bibtex
@inproceedings{Reshetouski11:TKI,
author = {Ilya Reshetouski and Alkhazur Manakov and Hans-Peter Seidel and Ivo Ihrke},
title = {Three-Dimensional Kaleidoscopic Imaging},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = 2011,
pages = {353--360},
}
author = {Ilya Reshetouski and Alkhazur Manakov and Hans-Peter Seidel and Ivo Ihrke},
title = {Three-Dimensional Kaleidoscopic Imaging},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = 2011,
pages = {353--360},
}