The analysis of facial expression temporal dynamics is of great importance for many real-world applications. Being able to automatically analyse facial muscle actions (Action Units...
We present ongoing work on a project for automatic recognition of spontaneous facial actions. Spontaneous facial expressions differ substantially from posed expressions, similar t...
Bjorn Braathen, Marian Stewart Bartlett, Gwen Litt...
—In this work we propose a dynamic-texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of te...
We propose a framework for estimation and analysis of temporal facial expression patterns of a speaker. The proposed system aims to learn personalized elementary dynamic facial ex...
Ferda Ofli, Engin Erzin, Yucel Yemez, A. Murat Tek...
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...