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Identity-aware Convolutional Neural Networks for Facial Expression Recognition

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut784-792
JulkaisuJournal of Systems Engineering and Electronics
Vuosikerta28
Numero4
DOI - pysyväislinkit
TilaJulkaistu - 14 syyskuuta 2017
OKM-julkaisutyyppiA1 Alkuperäisartikkeli

Tiivistelmä

Facial expression recognition is a hot topic in computer vision, but it remains challenging due to the feature inconsistency caused by person-specific characteristics of facial expressions. To address such a challenge, and inspired by the recent success of deep identity network (DeepID-Net) for face identification, this paper proposes a novel deep learning based framework for recognising human expressions with facial images. Compared to the existing deep learning methods, our proposed framework, which is based on multi-scale global images and local facial patches, can significantly achieve a better performance on facial expression recognition. Finally, we verify the effectiveness of our proposed framework through experiments on the public benchmarking datasets JAFFE and extended Cohn-Kanade (CK+).

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