Estimation Of Facial Action Intensities On 2D And 3D Data
Year: 2011
Type: article
Abstract: The paradigm of Facial Action Coding System (FACS) offers a comprehensive solution for facial expression measurements to researchers. FACS defines atomic expression components called Action Units (AUs) and describes their strength on a five-point scale. Despite considerable progress in AU detection, the AU intensity estimation has not been much investigated. We propose SVM-based regression on AU feature space, and investigated person-independent estimation of 25 AUs that appear singly or in various combinations. Our method is novel in that we use regression for estimating intensities and comparatively evaluate the performances of 2D and 3D modalities. The proposed technique shows improvements over the state-of-the-art person-independent estimation, and that especially the 3D modality offers significant advantages for intensity coding. We have also found that fusion of 2D and 3D can boost the estimation performance, especially when modalities compensate for each other’s shortcomings. 1.
DOI: 10.5281/zenodo.42309
Authors: Bilge, Mustafa, Sankur, B., Savran, Arman
Institution: Boğaziçi University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2119640399