Uncovering Topological Structures in Unstructured Data

Abstract

This research project aims to examine topological structures of scanned point-cloud data. It has two stages. In the first stage, we analyzed scan data and extracted topologically critical points. We used these critical points to enhance the robustness of slicing scan data in additive manufacturing. In the second stage, we focused on how to analyze scan data of a population of objects. In this context, we discovered novel ways of computing covariance matrix of shape population and developed methods for optimizing correspondence across a shape population.

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Document Details

Document Type
Technical Report
Publication Date
Apr 20, 2015
Accession Number
ADA619112

Entities

People

  • Keith Bowman
  • Xiaoping Qian

Organizations

  • Illinois Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Additive Manufacturing
  • Air Force
  • Air Force Research Laboratories
  • Construction
  • Contracts
  • Covariance
  • Electronic Mail
  • Engineering
  • Geometric Processing
  • Geometry
  • Manufacturing
  • Models
  • Scientific Research
  • Statistical Shape Models
  • Stereolithography
  • Three Dimensional
  • Vascular Diseases

Readers

  • Computer Vision.
  • Regression Analysis.
  • Systems Analysis and Design