首页|Lightweight facial expression estimation for mobile computing in portable device
Lightweight facial expression estimation for mobile computing in portable device
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NETL
NSTL
Wiley
Facial expression recognition has been studied for many years, especially withthe development of deep learning. However, the existing researches still havethe following two issues. Firstly, the intensity of facial expression is neglected.Secondly, the deep learning based approaches cannot be directly deployed in thedevices with limited resources. In order to tackle these two issues, this paper proposesa lightweight facial expression estimation method using a shallow ordinalregression algorithm, which is deployed in a portable smart device for mobilecomputing in IoTs. Compared with classification based facial expression recognitionmethods, ordinal regression considers the intensity of facial expression toachieve bettermean absolute error (MAE), which is validated by experiments onseveral public facial expression datasets. The simulation in portable device alsodemonstrates its effectiveness for mobile computing.
facial expression estimationinternet of thingslightweight modelmobile computing
Jinming Liu
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School of Software Engineering, JilinTechnology College of ElectronicInformation, Jilin, China
NETL
NSTL
Wiley
