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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Conference papers
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https://hal-supelec.archives-ouvertes.fr/hal-00657734
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Submitted on : Monday, January 9, 2012 - 10:37:03 AM
Last modification on : Tuesday, May 14, 2019 - 11:02:10 AM

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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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