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Publicatie

Framework for Combination Aware AU Intensity Recognition

Boekbijdrage - Boekhoofdstuk Conferentiebijdrage

We present a framework for combination aware AU
intensity recognition. It includes a feature extraction approach
that can handle small head movements which does not require
face alignment. A three layered structure is used for the AU
classification. The first layer is dedicated to independent AU
recognition, and the second layer incorporates AU combination
knowledge. At a third layer, AU dynamics are handled based on
variable duration semi-Markov model. The first two layers are
modeled using extreme learning machines (ELMs). ELMs have
equal performance to support vector machines but are computationally
more efficient, and can handle multi-class classification
directly. Moreover, they include feature selection via manifold
regularization. We show that the proposed layered classification
scheme can improve results by considering AU combinations as
well as intensity recognition.
Boek: IEEE 6th International Conference on Affective Computing and Intelligent Interaction (ACII2015)
Pagina's: 602
Aantal pagina's: 608
Jaar van publicatie:2015
Trefwoorden:FACS, ELM, AU combination aware hierarchical classification, VDHMM
  • ORCID: /0000-0002-1774-2970/work/83442852
  • Scopus Id: 84964049121
  • WoS Id: 000377887000089