Exploring the Effect of Illumination on Automatic Expression Recognition using the ICT-3DRFE Database

Abstract

One of the main challenges in facial expression recognition is illumination invariance. Our long-term goal is to develop a system for automatic facial expression recognition that is robust to light variations. In this paper, we introduce a novel 3D Relightable Facial Expression (ICT-3DRFE) database that enables experimentation in the fields of both computer graphics and computer vision. The database contains 3D models for 23 subjects and 15 expressions, as well as photometric information that allow for photorealistic rendering. It is also facial action units annotated, using FACS standards. Using the ICT-3DRFE database we create an image set of different expressions/illuminations to study the effect of illumination on automatic expression recognition. We compared the output scores from automatic recognition with expert FACS annotations and found that they agree when the illumination is uniform. Our results show that the output distribution of the automatic recognition can change significantly with light variations and sometimes causes the discrimination of two different expressions to be diminished. We propose a ratio-based light transfer method, to factor out unwanted illuminations from given images and show that it reduces the effect of illumination on expression recognition.

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Document Details

Document Type
Technical Report
Publication Date
Nov 04, 2011
Accession Number
ADA560069

Entities

People

  • Abhijeet Ghosh
  • Giota Stratou
  • Louis-Philippe Morency
  • Paul Debevec

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Automatic
  • Cameras
  • Classification
  • Computer Graphics
  • Computers
  • Databases
  • Geometry
  • High Resolution
  • Identification
  • Information Science
  • Machine Learning
  • Photographs
  • Recognition
  • Reflectance
  • Standards
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Circadian Sleep-Wake Regulation and Chronobiology
  • Computer Vision.
  • Molecular Genetics

Technology Areas

  • AI & ML