Affiliation:
1. University of Toronto, Canada
2. University of Toronto, Canada and Adobe Research, Canada
Abstract
We introduce a statistical extension of the classic Poisson Surface Reconstruction algorithm for recovering shapes from 3D point clouds. Instead of outputting an implicit function, we represent the reconstructed shape as a modified Gaussian Process, which allows us to conduct statistical queries (e.g., the likelihood of a point in space being on the surface or inside a solid). We show that this perspective: improves PSR's integration into the online scanning process, broadens its application realm, and opens the door to other lines of research such as applying task-specific priors.
Funder
NSERC Vanier
New Frontiers of Research Fund
Ontario Early Research Award
Canada Research Chairs Program
Sloan Research Fellowship
DSI Catalyst Grant
NSERC Discovery
Adobe Research Fellowship
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design
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