Face recognition: elastic relation encoding and structural matching

R. Lee, J. Liu, Jia You

Research output: Journal article publicationConference articleAcademic researchpeer-review

10 Citations (Scopus)


Face recognition relies heavily on feature extraction and the classification of features in the process of pattern recognition. Existing methods tend to address the problem with some tradeoff between the speed and accuracy in the process. In this paper, a system known as Elastic Graph Dynamic Link Model (EGDLM) is proposed to provide an effective and reliable solution. The model simplifies the traditional Dynamic Link Model and integrates it with the Active Contour Model for feature extraction. The complex facial pattern matching process is reduced to an elastic graph system matching of facial contours. A database of 1020 facial images was used for model testing and experimental speed by more than 1000 times, and an overall recognition rate of over 85%.
Original languageEnglish
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 1 Dec 1999
Event1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Japan
Duration: 12 Oct 199915 Oct 1999

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering


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