Shaped-Based Recognition of 3D Objects From 2D Projections

Abstract

We present an object recognition algorithm that uses model and image line features to locate complex objects in high clutter environments. Corresponding line features are determined by a three-stage process. The first stage generates a large number of approximate pose hypotheses from correspondence of one or two lines in the model and image. Next, pose hypotheses from the previous stage are quickly evaluated and ranked by a comparison of local image neighborhoods to the corresponding local model neighborhoods. Fast nearest neighbor and range search algorithms are used to implement a distance measure that is unaffected by clutter and partial occlusion. The ranking of pose hypotheses is invariant to changes in image scale, orientation, and partially invariant to affine distortion. Finally, a robust pose estimation algorithm is applied for refinement and verification, starting from the few best approximate poses produced by the previous stages. Experiments on real images demonstrate robost recognition of partially occluded objects in very high clutter environments.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2006
Accession Number
ADA459273

Entities

People

  • Daniel Dementhon
  • Philip David

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Base Lines
  • Computer Vision
  • Detection
  • Detectors
  • Environment
  • Geometry
  • Hypotheses
  • Identification
  • Image Processing
  • Object Recognition
  • Orientation (Direction)
  • Probability
  • Recognition
  • Three Dimensional
  • Trees (Data Structures)
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Human-Computer Interaction (HCI).
  • Sensor Fusion and Tracking Systems.