Mid-Level Vision and Recognition of Non-Rigid Objects.

Abstract

We address mid-level vision for the recognition of non-rigid objects. We align model and image using frame curves - which are object or "figure/ground" skeletons. Frame curves are computed, without discontinuities, using Curved Inertia Frames, a provably global scheme implemented on the Connection Machine, based on: non-cartisean networks; a definition of curved axis of inertia; and a ridge detector. I present evidence against frame alignment in human perception. This suggests: frame curves have a role in figure/ground segregation and in fuzzy boundaries; their outside/near/top/incoming regions are more salient; and that perception begins by selling a reference frame (prior to early vision), and proceeds by processing convex structures. (AN)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1993
Accession Number
ADA297984

Entities

People

  • J. B. Subirana-vilanova

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Autonomous Navigation
  • Birds
  • Change Detection
  • Collision Avoidance
  • Computer Vision
  • Detection
  • Detectors
  • Electrical Engineering
  • Geometry
  • Information Processing
  • Object Recognition
  • Psychology
  • Robots
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computer Vision.