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Abstract
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.
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.
| Original language | English |
|---|---|
| Title of host publication | IEEE 6th International Conference on Affective Computing and Intelligent Interaction (ACII2015) |
| Pages | 602 |
| Number of pages | 608 |
| Publication status | Published - 2015 |
| Event | IEEE 6th International Conference on Affective Computing and Intelligent Interaction - China, Xi'an , China Duration: 21 Sep 2015 → 24 Sep 2015 |
Conference
| Conference | IEEE 6th International Conference on Affective Computing and Intelligent Interaction |
|---|---|
| Country | China |
| City | Xi'an |
| Period | 21/09/15 → 24/09/15 |
Keywords
- FACS
- ELM
- AU combination aware hierarchical classification
- VDHMM
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SRP11: Strategic Research Programme: Processing of large scale multi-dimensional, multi-spectral, multi-sensorial and distributed data (M³D²)
Schelkens, P., Deligiannis, N., Jansen, B., Kuijk, M., Munteanu, A., Sahli, H., Steenhaut, K., Stiens, J., Schelkens, P., Cornelis, J. P., Kuijk, M., Munteanu, A., Sahli, H., Stiens, J. & Vounckx, R.
1/11/12 → 31/12/23
Project: Fundamental
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OZR2709: International Joint Research Group - Joint Laboratory on Audio Visual Signal Processing
Sahli, H. & Zhang, Y.
3/12/14 → 2/12/20
Project: Fundamental
-
IRP5: Objectifying Assessment of Human Emotional Processing and Expression of Clinical and Psychotherapy Applications (EMO-App)
Sahli, H., Vandekerckhove, M. & Kerckhofs, E.
1/04/13 → 31/03/18
Project: Fundamental