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A Baum-Welch Algorithm for Noisy Vector Fields for Classification and Synthesis of Textures Using Non-Symmetric Half-Plane
Author(s) -
Paul M. Baggenstoss
Publication year - 2008
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Reports
DOI - 10.21236/ada494616
Subject(s) - vector field , algorithm , hidden markov model , computation , plane (geometry) , field (mathematics) , series (stratigraphy) , mathematics , pattern recognition (psychology) , function (biology) , computer science , artificial intelligence , geometry , pure mathematics , paleontology , evolutionary biology , biology
: In this paper we present a statistical model with a non-symmetric half-plane (NSHP) region of support for two-dimensional continuous-valued vector fields. It has the simplicity, efficiency, and ease of use of the well-known hidden Markov model (HMM) and associated Baum-Welch algorithms for time-series and other one-dimensional problems. At the same time, it is able to learn textures on a two-dimensional field. We describe a fast approximate forward procedure for computation of the joint probability density function (PDF) of the vector field as well as an approximate Baum-Welch algorithm for parameter re-estimation. We test the method using synthetic textures.

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