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Facial Landmark Localization and Feature Extraction for Therapeutic Face Exercise Classification

  • Cornelia LanzEmail author
  • Birant Sibel Olgay
  • Joachim Denzler
  • Horst-Michael Gross
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 458)

Abstract

In this work, we examine landmark localization and feature extraction approaches for the unexplored topic of therapeutic facial exercise recognition. Our goal is to automatically discriminate nine therapeutic exercises that have been determined in cooperation with speech therapists. We use colour, 2.5D and 3D image data that was recorded using Microsoft’s Kinect. Our features comprise statistical descriptors of the face surface curvature as well as characteristic profiles that are derived from face landmarks. For the nine facial exercises, we yield an average recognition accuracy of about \(91\,\%\) in conjunction with manually labeled landmarks. Additionally, we introduce a combined method for automatic landmark localization and compare the results to landmark positions obtained from Active Appearance Model fitting as well as manual labeling. The combined localization method exhibits increased robustness in comparison to AAMs.

Keywords

Facial expressions Curvature analysis Point signatures Line profiles Therapeutic exercises 

Notes

Acknowledgements

We would like to thank the m&i Fachklinik Bad Liebenstein (in particular Prof. Dr. med. Gustav Pfeiffer, Eva Schillikowski) and Logopädische Praxis Irina Stangenberger, who supported our work by giving valuable insights into rehabilitation and speech-language therapy requirements and praxis. This work is partially funded by the TMBWK ProExzellenz initiative, Graduate School on Image Processing and Image Interpretation.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Cornelia Lanz
    • 1
    Email author
  • Birant Sibel Olgay
    • 1
  • Joachim Denzler
    • 2
  • Horst-Michael Gross
    • 1
  1. 1.Neuroinformatics and Cognitive Robotics LabIlmenau University of TechnologyIlmenauGermany
  2. 2.Computer Vision GroupFriedrich Schiller University JenaJenaGermany

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