Stochastic Heat Kernel Estimation on Sampled Manifolds

The heat kernel is a fundamental geometric object associated to every Riemannian manifold, used across applications in computer vision, graphics, and machine learning. In this article, we propose a novel computational approach to estimating the heat kernel of a statistically sampled manifold (e.g. m...

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Bibliographic Details
Published in:	Computer graphics forum Vol. 36; no. 5; pp. 131 - 138
Main Authors:	Aumentado‐Armstrong, T., Siddiqi, K.
Format:	Journal Article
Language:	English
Published:	Oxford Blackwell Publishing Ltd 01.08.2017
Subjects:	Brownian motion Categories and Subject Descriptors (according to ACM CCS) Computer simulation Computer vision Density Economic models G.3 [Mathematics of Computing]: Probability and Statistics—Probabilistic Algorithms I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling—Geometric Algorithms, Languages, and Systems Machine learning Manifolds (mathematics) Numerical integration Parallel processing Riemann manifold Statistical analysis Statistical methods Three dimensional models Trajectory analysis
ISSN:	0167-7055, 1467-8659
Online Access:	Get full text
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