Computational Methods for Flow Problems - Parallel Algorithms, Flow Control, and Novel Approaches.

Abstract

We have created an object recognition system, in the context of the general goal of contributing to the development of a visual architecture. The system makes use of wavelet transforms, of dynamic link matching, and is of general neural style. We have implemented the system in several versions, as an object-oriented modular program on a workstation, and as a parallel farm structure on an array of transputers. Object recognition from camera images is invariant to translation, scaling and rotation in the image plane, and is robust with respect to lighting and to rotation in depth. We have tested the system on the task of recognizing human faces. With galleries of about 90 faces, the system achieved highly confident recognition on ca. 85% of the input images.

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Document Details

Document Type
Technical Report
Publication Date
Jul 31, 1992
Accession Number
ADA295126

Entities

People

  • Christoph Von Der Malsburg
  • Gaudiot

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Computer Programming
  • Computer Science
  • Computer Vision
  • Computers
  • Construction
  • Data Storage Systems
  • Databases
  • Detectors
  • Neural Networks
  • Object Recognition
  • Parallel Computing
  • Parallel Processing
  • Recognition
  • Self Organizing Systems
  • Wavelet Transforms

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Parallel and Distributed Computing.