Research Area:  Machine Learning

Abstract:

We investigate facial expression recognition using state-of-the-art classification models. Recently, CNNs have been extensively used for face recognition. However, CNNs have not been thoroughly evaluated for facial expression recognition. In this paper, we train and test a CNN model for facial expression recognition. The performance of the CNN model is used as benchmark for evaluating other pre-trained deep CNN models. We evaluate the performance of Inception and VGG which are pre-trained for object recognition, and compare these with VGG-Face which is pre-trained for face recognition. All experiments are performed on publicly available face databases, namely, CK+, JAFFE and FACES.

Keywords:  
Deep Learning
Facial Expression Recognition
Machine Learning

Author(s) Name:   Atul Sajjanhar; ZhaoQi Wu; Quan Wen

Publisher name:  IEEE

DOI:  10.1109/DICTA.2018.8615843

Volume Information:  

Paper Link:   https://ieeexplore.ieee.org/abstract/document/8615843