DocumentCode :
1797843
Title :
Intelligent Facial Action and emotion recognition for humanoid robots
Author :
Li Zhang ; Hossain, Abrar ; Ming Jiang
Author_Institution :
Dept. of Comput. Sci. & Digital Technol., Northumbria Univ., Newcastle upon Tyne, UK
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
739
Lastpage :
746
Abstract :
This research focuses on the development of a realtime intelligent facial emotion recognition system for a humanoid robot. In our system, Facial Action Coding System is used to guide the automatic analysis of emotional facial behaviours. The work includes both an upper and a lower facial Action Units (AU) analyser. The upper facial analyser is able to recognise six AUs including Inner and Outer Brow Raiser, Upper Lid Raiser etc, while the lower facial analyser is able to detect eleven AUs including Upper Lip Raiser, Lip Corner Puller, Chin Raiser, etc. Both of the upper and lower analysers are implemented using feedforward Neural Networks (NN). The work also further decodes six basic emotions from the recognised AUs. Two types of facial emotion recognisers are implemented, NN-based and multi-class Support Vector Machine (SVM) based. The NN-based facial emotion recogniser with the above recognised AUs as inputs performs robustly and efficiently. The Multi-class SVM with the radial basis function kernel enables the robot to outperform the NN-based emotion recogniser in real-time posed facial emotion detection tasks for diverse testing subjects.
Keywords :
emotion recognition; face recognition; humanoid robots; image coding; intelligent robots; object detection; radial basis function networks; robot vision; support vector machines; AU analyser; NN-based emotion recognition; SVM-based emotion recognition; emotion recognition; emotional facial behaviour; facial action coding system; facial action units analyser; facial emotion detection tasks; feedforward neural networks; humanoid robots; intelligent facial action recognition; multiclass support vector machine; radial basis function kernel; Emotion recognition; Face; Face recognition; Hidden Markov models; Humanoid robots; Training; facial action; facial emotion recognition; neural network; support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
Type :
conf
DOI :
10.1109/IJCNN.2014.6889647
Filename :
6889647
Link To Document :
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