Systems Engineering and Electronics

• SOFTWARE ALGORITHM AND SIMULATION • Previous Articles     Next Articles

Identity-aware convolutional neural networks for facial expression recognition

Chongsheng Zhang1, Pengyou Wang1, Ke Chen2,*, and Joni-Kristian K¨am¨ ar¨ainen2   

  1. 1. The Big Data Research Center, Henan University, Kaifeng 475001, China;
    2. Department of Signal Processing, Tampere University of Technology, Tampere 33720, Finland
  • Online:2017-08-25 Published:2010-01-03


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+).