Birant Sibel Olgay
Ilmenau University of Technology, Germany
Friedrich Schiller University Jena, Germany
Facial Expressions, Curvature Analysis, Point Signatures, Line Profiles, Therapeutic Exercises.
Applications and Services
Computer Vision, Visualization and Computer Graphics
Medical Image Applications
In this work, we propose an approach for the unexplored topic of therapeutic facial exercise recognition using
depth images. In cooperation with speech therapists, we determined nine exercises that are beneficial for
therapy of patients suffering from dysfunction of facial movements. Our approach employs 2.5D images and
3D point clouds, which were recorded using Microsoft’s Kinect. Extracted features comprise the curvature
of the face surface and characteristic profiles that are derived using distinctive landmarks. We evaluate the
discriminative power and the robustness of the features with respect to the above-mentioned application scenario.
Using manually located face regions for feature extraction, we achieve an average recognition accuracy
of about 91% for the nine facial exercises. However in a real-world scenario manual localization of regions
for feature extraction is not feasible. Therefore, we additionally examine the robustness of the features and
show, that they are benefic
ial for a real-world, fully automated scenario as well.