Combining LGBP Histograms with AAM coefficients in the Multi-Kernel SVM framework to detect Facial Action Units - CentraleSupélec Access content directly
Conference Papers Year : 2011

Combining LGBP Histograms with AAM coefficients in the Multi-Kernel SVM framework to detect Facial Action Units

Abstract

This study presents a combination of geometric and appearance features used to automatically detect Action Units in face images. We use one multi-kernel SVM for each Action Unit we want to detect. The first kernel matrix is computed using Local Gabor Binary Pattern (LGBP) histograms and a histogram intersection kernel. The second kernel matrix is computed from AAM coefficients and a RBF kernel. During the training step, we combine these two type s of features using the recent SimpleMKL algorithm. SVM outputs are then filtered to exploit dynamic relationships between Action Units.
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Dates and versions

hal-00657734 , version 1 (09-01-2012)

Identifiers

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Thibaud Sénéchal, Vincent Rapp, Hanan Salam, Renaud Seguier, Kevin Bailly, et al.. Combining LGBP Histograms with AAM coefficients in the Multi-Kernel SVM framework to detect Facial Action Units. FG 2011, Mar 2011, Santa Barbara, United States. pp.860 - 865, ⟨10.1109/FG.2011.5771363⟩. ⟨hal-00657734⟩
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