Datasets
Toronto NeuroFace Dataset
A New Dataset for Facial Motion Analysis in Individuals with Neurological Disorders
Authors: Bandini, A., Rezaei, S., Guarin, D., Kulkarni, M., Lim, D., Boulos, M., Zinman, L., Yunusova, Y. & Taati, B.
Access the paper here
Abstract: In this paper, we present the first public dataset with videos of oro-facial gestures performed by individuals with orofacial impairment due to neurological disorders, such as amyotrophic lateral sclerosis (ALS) and stroke. Perceptual clinical scores from trained clinicians are provided as metadata. Manual annotation of facial landmarks is also provided for a subset of over 3300 frames. Through extensive experiments with multiple facial landmark detection algorithms, including state-of-the-art convolutional neural network (CNN) models, we demonstrated the presence of bias in the landmark localization accuracy of pretrained face alignment approaches in our participant groups. The pre-trained models produced a higher error in the two clinical groups compared to the age-matched healthy control subjects.We also demonstrated that this bias can be reduced by fine-tuning the existing approaches using data from the target population. The release of this dataset aims to propel the development of face alignment algorithms robust to the presence of oro-facial impairment, support the automatic analysis and recognition of oro-facial gestures, enhance the automatic identification of neurological diseases, as well as the estimation of disease severity from videos and images.
- Submit a data access request here
- Your request will be processed in 3 to 5 business days
- Please cite the following paper:
A. Bandini, S, Rezaei, D. Guarin, M. Kulkarni, D. Lim, M. Boulos, L. Zinman, Y. Yunusova, and B. Taati. A New Dataset for Facial Motion Analysis in Individuals with Neurological Disorders. IEEE J Biomed Health Inform. vol. 25, no. 4, pp. 1111-1119, April 2021, doi: 10.1109/JBHI.2020.3019242. - All documents and papers that report on research that use any of the NeuroFace Database will acknowledge this as follows:
“(Portions of) the research in this paper uses the Toronto NeuroFace Dataset collected by Dr. Yana Yunusova and the Vocal Tract Visualization and Bulbar Function Lab teams at UHN-Toronto Rehabilitation Institute and Sunnybrook Research Institute respectively, financially supported by the Michael J. Fox Foundation, NIH-NIDCD, Natural Sciences and Engineering Research Council, Heart and Stroke Foundation Canadian Partnership for Stroke Recovery and AGE-WELL NCE.” - Please send a copy of any document or papers that reports on research that uses the Toronto NeuroFace Databset to Dr. Yana Yunusova.