Title
Combining Deep Neural Network with Traditional Classifier to Recognize Facial Expressions
Abstract
Facial expressions are important in people’s daily communications. Recognising facial expressions also has many important applications in the areas such as healthcare and e-learning. Existing facial expression recognition systems have problems such as background interference. Furthermore, systems using traditional approaches like SVM (Support Vector Machine) have weakness in dealing with unseen images. Systems using deep neural network have problems such as requirement for GPU, longer training time and requirement for large memory. To overcome the shortcomings of pure deep neural network and traditional facial recognition approaches, this paper presents a new facial expression recognition approach which has image pre-processing techniques to remove unnecessary background information and combines deep neural network ResNet50 and a traditional classifier-- the multiclass model for Support Vector Machine to recognise facial expressions. The proposed approach has better recognition accuracy than traditional approaches like Support Vector Machine and doesn’t need GPU. We have compared 3 proposed frameworks with a traditional SVM approach against the Karolinska Directed Emotional Faces (KDEF) Database, the Japanese Female Facial Expression (JAFFE) Database and the extended Cohn-Kanade dataset (CK+), respectively. The experiment results show that the features extracted from the layer 49Relu have the best performance for these three datasets.
Year
DOI
Venue
2019
10.23919/IConAC.2019.8895084
2019 25th International Conference on Automation and Computing (ICAC)
Keywords
Field
DocType
Facial Expression Recognition,Deep Convolution Network,Support Vector Machine
Facial recognition system,Pattern recognition,Facial expression recognition,Support vector machine,Control engineering,Facial expression,Artificial intelligence,Engineering,Artificial neural network,Classifier (linguistics)
Conference
ISBN
Citations 
PageRank 
978-1-7281-2518-3
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Zixiang Fei142.45
Erfu Yang212626.99
David Li314717.08
Stephen Butler421.39
Winifred Ijomah500.34
Huiyu Zhou61303111.91