Experiments in Expression Recognition

Abstract

Despite the significant effort devoted to methods for expression recognition, suitable training and test databases designed explicitly for expression research have been largely neglected. Additionally, possible techniques for expression recognition within an Man-Machine-Interface (MMI) domain are numerous, but it remains unclear what methods are most effective for expression recognition. In response, this thesis describes the means by which an appropriate expression database has been generated and then enumerates the results of five different recognition methods as applied to that database. An analysis of the results of these experiments is given, and conclusions for future research based upon these results is put forth.

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Document Details

Document Type
Technical Report
Publication Date
Aug 16, 2005
Accession Number
ADA454701

Entities

People

  • James P. Skelley

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Behavioral Sciences
  • Cognitive Science
  • Computations
  • Computer Science
  • Computer Vision
  • Databases
  • Electrical Engineering
  • Engineering
  • Human-Machine Interaction
  • Human-Machine Interfaces
  • Image Processing
  • Information Science
  • Pattern Recognition
  • Recognition
  • Supervised Machine Learning

Readers

  • Cellular and Molecular Pathways of Apoptosis.
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design