Automatic facial analysis for objective assessment of facial paralysis

J.J. Soraghan, Brian O'Reilly, Shu He, Stewart McGrenary

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Abstract

Facial Paralysis is a condition causing decreased movement on one side of the face. A quantitative, objective and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents an approach based on the automatic analysis of patient video data. Facial feature localization and facial movement detection methods are discussed. An algorithm is presented to process the optical flow data to obtain the motion features in the relevant facial regions. Three classification methods are applied to provide quantitative evaluations of regional facial nerve function and the overall facial nerve function based on the House-Brackmann Scale. Experiments show the Radial Basis Function (RBF) Neural Network to have superior performance.
Original languageEnglish
Publication statusPublished - Dec 2009
Event1st International Conferfence on Computer Science from Algorithms to Applications (CSAA-2009) - Cairo, Egypt
Duration: 8 Jan 200910 Jan 2009

Conference

Conference1st International Conferfence on Computer Science from Algorithms to Applications (CSAA-2009)
CityCairo, Egypt
Period8/01/0910/01/09

Keywords

  • facial paralysis measurement
  • house-brackmann scale
  • optical flow
  • rbf neural network

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  • Impacts

    Improved diagnosis and benefit to patients with facial palsy from new measurement software

    John Soraghan (Participant)

    Impact: Impact - for External PortalHealth and welfare - new products, guidelines and services

    Cite this

    Soraghan, J. J., O'Reilly, B., He, S., & McGrenary, S. (2009). Automatic facial analysis for objective assessment of facial paralysis. 1st International Conferfence on Computer Science from Algorithms to Applications (CSAA-2009), Cairo, Egypt, .