Combining Deep Facial and Ambient Features for First Impression Estimation
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Dosyalar
Tarih
2016
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer International Publishing Ag
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
First impressions influence the behavior of people towards a newly encountered person or a human-like agent. Apart from the physical characteristics of the encountered face, the emotional expressions displayed on it, as well as ambient information affect these impressions. In this work, we propose an approach to predict the first impressions people will have for a given video depicting a face within a context. We employ pre-trained Deep Convolutional Neural Networks to extract facial expressions, as well as ambient information. After video modeling, visual features that represent facial expression and scene are combined and fed to a Kernel Extreme Learning Machine regressor. The proposed system is evaluated on the ChaLearn Challenge Dataset on First Impression Recognition, where the classification target is the Big Five personality trait labels for each video. Our system achieved an accuracy of 90.94% on the sequestered test set, 0.36% points below the top system in the competition.
Açıklama
14th European Conference on Computer Vision (ECCV) -- OCT 08-16, 2016 -- Amsterdam, NETHERLANDS
Anahtar Kelimeler
Personality traits, First impression, Deep learning, ELM, Face, Inferences, Competence
Kaynak
Computer Vision - Eccv 2016 Workshops, Pt Iii
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
9915
