A Facial-Expression Monitoring System for Improved Healthcare in Smart Cities

IEEE Access

Ghulam Muhammad¹  Mansour Alsulaiman¹  Syed Umar Amin¹  Ahmed Ghoneim²  Mohammed F. Alhamid² 

[1] Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;

关键词: Smart cities;    health monitoring;    facial expression;    CS-LBP;    SVM;    GMM;   

DOI  :  10.1109/ACCESS.2017.2712788

来源: DOAJ

【 摘 要 】

Human facial expressions change with different states of health; therefore, a facial-expression recognition system can be beneficial to a healthcare framework. In this paper, a facial-expression recognition system is proposed to improve the service of the healthcare in a smart city. The proposed system applies a bandlet transform to a face image to extract sub-bands. Then, a weighted, center-symmetric local binary pattern is applied to each sub-band block by block. The CS-LBP histograms of the blocks are concatenated to produce a feature vector of the face image. An optional feature-selection technique selects the most dominant features, which are then fed into two classifiers: a Gaussian mixture model and a support vector machine. The scores of these classifiers are fused by weight to produce a confidence score, which is used to make decisions about the facial expression's type. Several experiments are performed using a large set of data to validate the proposed system. Experimental results show that the proposed system can recognize facial expressions with 99.95% accuracy.

【 授权许可】

Unknown