Model for predicting perception of facial action unit activation using virtual humans

Rachel McDonnell, Katja Zibrek, Emma Carrigan, Rozenn Dahyot

Abstract: Highlights•The paper presents the first experiment on perception of perceptibility of Facial Action Units under different activation levels, which allows us to list the importance of blendshape expressions. Our main contribution is our perceptual models for perceptibility of facial action units and we provide our GitHub repository with the data and models in R-Code, allowing others to build on our data investigating a larger range of faces, viewpoints and facial action units, or to try different non-linear models such as neural networks.