Multimodal Fusion of Audio, Scene, and Face Features for First Impression Estimation
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Dosyalar
Tarih
2016
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE Computer Soc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Affective computing, particularly emotion and personality trait recognition, is of increasing interest in many research disciplines. The interplay of emotion and personality shows itself in the first impression left on other people. Moreover, the ambient information, e.g. the environment and objects surrounding the subject, also affect these impressions. In this work, we employ pre-trained Deep Convolutional Neural Networks to extract facial emotion and ambient information from images for predicting apparent personality. We also investigate Local Gabor Binary Patterns from Three Orthogonal Planes video descriptor and acoustic features extracted via the popularly used openSMILE tool. We subsequently propose classifying features using a Kernel Extreme Learning Machine and fusing their predictions. The proposed system is applied to the ChaLearn Challenge on First Impression Recognition, achieving the winning test set accuracy of 0.913, averaged over the Big Five personality traits.
Açıklama
23rd International Conference on Pattern Recognition (ICPR) -- DEC 04-08, 2016 -- Mexican Assoc Comp Vis Robot & Neural Comp, Cancun, MEXICO
Anahtar Kelimeler
Extreme Learning-Machine
Kaynak
2016 23rd International Conference on Pattern Recognition (Icpr)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
