BlurTags: Spatially Varying PSF Estimation with Out-of-Focus Patterns
In this paper, we consider the problem of animation reconstruction, i.e., the
reconstruction of shape and motion of a deformable object from dynamic
3D scanner data, without using user provided template models. Unlike pre-
vious work that addressed this problem, we do not rely on locally conver-
gent optimization but present a system that can handle fast motion, tem-
porally disrupted input, and can correctly match objects that disappear for
extended time periods in acquisition holes due to occlusion. Our approach
is motivated by cartography: We first estimate a few landmark correspon-
dences, which are extended to a dense matching and then used to recon-
struct geometry and motion. We propose a number of algorithmic building
blocks: a scheme for tracking landmarks in temporally coherent and inco-
herent data, an algorithm for robust estimation of dense correspondences
under topological noise, and the integration of local matching techniques to
refine the result. We describe and evaluate the individual components and
propose a complete animation reconstruction pipeline based on these ideas.
We evaluate our method on a number of standard benchmark data sets and
show that we can obtain correct reconstructions in situations where other
techniques fail completely or require additional user guidance such as a
template model.
Projects
Gordon Wetzstein, Ivo Ihrke, Douglas Lanman, Wolfgang Heidrich
Computer Graphics Forum 2011
Go to project listComputer Graphics Forum 2011
Abstract
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.
Project Page Slides Bibtex
@Article{Wetzstein11:CPI,
author = {Gordon Wetzstein, Ivo Ihrke, Douglas Lanman, and Wolfgang Heidrich},
title = {Computational Plenoptic Imaging},
journal = {Computer Graphics Forum},
volume = {30},
number = {8},
year = {2011},
pages = {2397--2426},
publisher = {Blackwell Publishing},
}
author = {Gordon Wetzstein, Ivo Ihrke, Douglas Lanman, and Wolfgang Heidrich},
title = {Computational Plenoptic Imaging},
journal = {Computer Graphics Forum},
volume = {30},
number = {8},
year = {2011},
pages = {2397--2426},
publisher = {Blackwell Publishing},
}