Action unit intensity estimation using hierarchical partial least squares

Tobias Gehrig, Ziad Al-Halah, Hazim Kemal Ekenel, Rainer Stiefelhagen

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

7 Atıf (Scopus)

Özet

Estimation of action unit (AU) intensities is considered a challenging problem. AUs exhibit high variations among the subjects due to the differences in facial plasticity and morphology. In this paper, we propose a novel framework to model the individual AUs using a hierarchical regression model. Our approach can be seen as a combination of locally linear Partial Least Squares (PLS) models where each one of them learns the relation between visual features and the AU intensity labels at different levels of details. It automatically adapts to the non-linearity in the source domain by adjusting the learned hierarchical structure. We evaluate our approach on the benchmark of the Bosphorus dataset and show that the proposed approach outperforms both the 2D state-of-the-art and the plain PLS baseline models. The generalization to other datasets is evaluated on the extended Cohn-Kanade dataset (CK+), where our hierarchical model outperforms linear and Gaussian kernel PLS.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781479960262
DOI'lar
Yayın durumuYayınlandı - 17 Tem 2015
Etkinlik11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015 - Ljubljana, Slovenia
Süre: 4 May 20158 May 2015

Yayın serisi

Adı2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015

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???event.eventtypes.event.conference???11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
Ülke/BölgeSlovenia
ŞehirLjubljana
Periyot4/05/158/05/15

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Publisher Copyright:
© 2015 IEEE.

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