Generalized Image Acquisition and Analysis

Animation Cartography - Intrinsic Reconstruction of Shape and Motion

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

State of the Art in Computational Plenoptic Imaging

Gordon Wetzstein, Ivo Ihrke, Douglas Lanman, Wolfgang Heidrich
In: STAR Proceedings of EUROGRAPHICS 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.
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Bibtex

@inproceedings{Wetzstein11:STAR,
author = {Gordon Wetzstein and Ivo Ihrke and Douglas Lanman and Wolfgang Heidrich},
title = {State of the Art in Computational Plenoptic Imaging},
booktitle = {STAR Proceedings of Eurographics},
year = 2011,
pages = {25--48},
}
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