Recognizing 3 D Objects from 2D Images Using Structural Knowledge Base of Genetic Views

Abstract

Model-based object recognition is an essential task for mobile robotics and assembly. Given an image of a scene containing one or more objects from unknown viewpoints, the goal is to efficiently recognize those objects for which there is sufficient evidence. At the University of Massachusetts, we are developing a model-based object recognition system which is capable of recognizing objects from a large data base of models and from arbitrary viewpoints. Contents: Overview; Extraction of Straight Lines; The View Sphere for Curved Surfaces; Reconstruction of Surfaces From Multiple Views; Predictions and the Prediction Hierarchy Compiler.

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Document Details

Document Type
Technical Report
Publication Date
Aug 31, 1988
Accession Number
ADA207875

Entities

People

  • Allen R. Hanson

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Change Detection
  • Computer Vision
  • Convex Bodies
  • Databases
  • Detection
  • Geometric Forms
  • Geometry
  • Identification
  • Image Processing
  • Image Recognition
  • Object Recognition
  • Pattern Recognition
  • Recognition
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Linguistics
  • Image Processing and Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Biotechnology