Identity-aware Convolutional Neural Networks for Facial Expression Recognition
Research output: Contribution to journal › Article › Scientific › peer-review
|Journal||Journal of Systems Engineering and Electronics|
|Publication status||Published - 14 Sep 2017|
|Publication type||A1 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+).