A Baum-Welch Algorithm for Noisy Vector Fields for Classification and Synthesis of Textures Using Non-Symmetric Half-Plane

Abstract

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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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2008
Accession Number
ADA494616

Entities

People

  • Paul Baggenstoss

Organizations

  • Naval Undersea Warfare Center

Tags

Communities of Interest

  • Air Platforms
  • Counter WMD

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Bayes Theorem
  • Classification
  • Computations
  • Data Science
  • Hidden Markov Models
  • Markov Models
  • Mathematics
  • Models
  • Probabilistic Models
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Three Dimensional
  • Two Dimensional

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Fluid Dynamics.
  • Statistical inference.