Tampere University of Technology

TUTCRIS Research Portal

Identity-aware Convolutional Neural Networks for Facial Expression Recognition

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Pages (from-to)784-792
JournalJournal of Systems Engineering and Electronics
Issue number4
Publication statusPublished - 14 Sep 2017
Publication typeA1 Journal article-refereed


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+).

Publication forum classification

Field of science, Statistics Finland