A Sheaf-Theoretic/Bayesian Approach for Shape Representation

Abstract

A point to surface matching algorithm for purposes of matching 3D point cloud data to CAD models is developed. By discretization of the unknown transformation parameters and using assignment correspondence modeling the resulting objective function is a multilinear programming problem with decoupled linear constraints. Mathematics software for the optimization algorithm and model setup is provided. The inputs for this code are the CAD models and point cloud 3D data.

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Document Details

Document Type
Technical Report
Publication Date
Oct 31, 2010
Accession Number
ADA538844

Entities

People

  • Kirk Sturtz

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Artificial Intelligence
  • Bayesian Networks
  • Computer Programming
  • Computer Vision
  • Mathematics
  • Models
  • Object Recognition
  • Optimization
  • Point Clouds
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Target Recognition
  • Two Dimensional

Readers

  • Computer Vision.
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms