Face Recognition Under Varying Pose.

Abstract

While researchers in computer vision and pattern recognition have worked on automatic techniques for recognizing faces for the last 20 years, most systems specialize on frontal views of the face. We present a face recognizer that works under varying pose, the difficult part of which is to handle face rotations in depth. Building on successful template-based systems, our basic approach is to represent faces with templates from multiple model views that cover different poses from the viewing sphere. Our system has achieved a recognition rate of 98% on a data base of 62 people containing 10 testing and 15 modelling views per person.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1993
Accession Number
ADA290205

Entities

People

  • David J. Beymer

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Cameras
  • Computational Science
  • Computer Vision
  • Databases
  • Detection
  • Information Science
  • Information Systems
  • Neural Networks
  • Object Recognition
  • Pattern Recognition
  • Recognition
  • Rotation
  • Standards
  • Template Patterns

Fields of Study

  • Computer science

Readers

  • Computer Vision.

Technology Areas

  • AI & ML