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Conference Paper

Reconstruction of Deforming Geometry from Time-Varying Point Clouds

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Wand,  Michael
Computer Graphics, MPI for Informatics, Max Planck Society;

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Jenke,  Philipp
Computer Graphics, MPI for Informatics, Max Planck Society;

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Bokeloh,  Martin
Computer Graphics, MPI for Informatics, Max Planck Society;
International Max Planck Research School, MPI for Informatics, Max Planck Society;

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Citation

Wand, M., Jenke, P., Huang, Q.-X., Bokeloh, M., Guibas, L., & Schilling, A. (2007). Reconstruction of Deforming Geometry from Time-Varying Point Clouds. In D. Fellner, & S. Spencer (Eds.), SGP 2007: Fifth Eurographics Symposium on Geometry Processing (pp. 49-58). Aire-la-Ville, Switzerland: Eurographics Association.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-207A-D
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.