Reconstruction of Deforming Geometry from Time-Varying Point Clouds
Loading...
Date
2007
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In this paper, we describe a system for the reconstruction of deforming geometry from a time sequence of unstructured, noisy point clouds, as produced by recent real-time range scanning devices. Our technique reconstructs both the geometry and dense correspondences over time. Using the correspondences, holes due to occlusion are filled in from other frames. Our reconstruction technique is based on a statistical framework: The reconstruction should both match the measured data points and maximize prior probability densities that prefer smoothness, rigid deformation and smooth movements over time. The optimization procedure consists of an inner loop that optimizes the 4D shape using continuous numerical optimization and an outer loop that infers the discrete 4D topology of the data set using an iterative model assembly algorithm. We apply the technique to a variety of data sets, demonstrating that the new approach is capable of robustly retrieving animated models with correspondences from data sets suffering from significant noise, outliers and acquisition holes.
Description
@inproceedings{:10.2312/SGP/SGP07/049-058,
booktitle = {Geometry Processing},
editor = {Alexander Belyaev and Michael Garland},
title = {{Reconstruction of Deforming Geometry from Time-Varying Point Clouds}},
author = {Wand, Michael and Jenke, Philipp and Huang, Qixing and Bokeloh, Martin and Guibas, Leonidas and Schilling, Andreas},
year = {2007},
publisher = {The Eurographics Association},
ISSN = {1727-8384},
ISBN = {978-3-905673-46-3},
DOI = {/10.2312/SGP/SGP07/049-058}
}