Adaptive color space switching for face tracking in multi-colored lighting environments

Helman Stern, Boris Efros

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

94 Scopus citations

Abstract

There are many studies that use color space models (CSM) for detection of faces in an image. Most researchers a priori select a given CSM, and proceed to use the selected model for color segmentation of the face by constructing a color distribution model (CDM). There is limited work on finding the overall best CSM. We develop a procedure to adaptively change the CSM throughout the processing of a video. We show that this works in environments where the face moves through multi-positioned light sources with varying types of illumination. A test of the procedure using the 2D color space models; RG, rg, HS, YQ and CbCr found that switching between the color spaces resulted in increased tracking performance. In addition, we have proposed a new performance measure for evaluating color-tracking algorithms, which include both accuracy and robustness of the tracking window. The methodology developed can be used to find the optimal CSM-CDM combination in adaptive color tracking systems.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002
PublisherInstitute of Electrical and Electronics Engineers
Pages249-254
Number of pages6
ISBN (Print)0769516025, 9780769516028
DOIs
StatePublished - 1 Jan 2002
Event5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002 - Washington, DC, United States
Duration: 20 May 200221 May 2002

Publication series

NameProceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002

Conference

Conference5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002
Country/TerritoryUnited States
CityWashington, DC
Period20/05/0221/05/02

Keywords

  • adaptive color segmentation
  • color segmentation
  • color space model selection
  • face tracking
  • image processing

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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