Facial expression is one of the most effective means for human beings to indicate emotions, feelings and intentions. Literature shows that facial expression contributed to about 55% effect of overall emotion expression during social interactions. Therefore, significant progress in facial emotion recognition has been witnessed in cognitive, neuroscience and computational intelligence fields. On top of that EEG base emotion detection has also shown promising performance in real-time emotion recognition (B. Nakisa et al. 2018). The combination of EEG and vision-based emotion, will provide an emotion recognition system that is robust to variations, such as illumination, rotation and pose. Although many applications employ geometric-based, appearance-based or hybrid methods for automatic facial expression recognition, it is still a difficult and challenging task to recognize facial expressions with high accuracy because of the subtlety and variability of facial expressions, especially during the natural human-computer interaction. Another challenging task is to model the recognised emotions in appropriate intentions and apply them respectively.
This project aims to provide flexible, cost-effective, robust and accurate intent detection system based on EEG and vision-based emotion recognition to model an automatic cognitive behavioural therapy (CBT) for drug rehabilitation. The two novel aspects of this project are as follows:
• Combination of EEG signals and computer vision for automatic facial emotion recognition.
• Integrating intention detection with automatic CBT for drug rehabilitation.
CBT is a talking therapy that can help to manage problems by changing the way of thinking and behaviour (E. E. Devito et al. 2018). CBT has also shown very effective in treating various mental disorders such as panic disorder, obsessive-compulsive disorder, depression, anxiety and drug addiction. The practical side of the project will involve the application of state-of-the-art machine learning and signal processing techniques for intent detection and emotion recognition in a real-life scenario.
The principal supervisor for this project is Kamlesh Mistry.
Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.
For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/
Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF19/EE/CIS/MISTRY) will not be considered.
Deadline for applications: Friday 25 January 2019
Start Date: 1 October 2019
Northumbria University is an equal opportunities provider and in welcoming applications for studentships from all sectors of the community we strongly encourage applications from women and under-represented groups.
The studentship is available to Students Worldwide, and covers full fees and a full stipend, paid for three years at RCUK rates (for 2018/19, this is £14,777 pa).
• Kamlesh Mistry, Li Zhang, Siew Chin Neoh, Chee Peng Lim, Benjamin Fielding, A micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion Recognition, IEEE transaction on Cybernetics, 2017.
• Siew Chin Neoh, Li Zhang, Kamlesh Mistry, Mohammed Alamgir Hossain, Chee Peng Lim, Nauman Aslam, Philip Kinghorn, Intelligent facial emotion recognition using a layered encoding cascade optimization model, Applied Soft Computing, 2015.
• Li Zhang, Kamlesh Mistry, Siew Chin Neoh, Chee Peng Lim, Intelligent Facial Emotion Recognition Using Moth-Firefly Optimization, Knowledge-Based Systems, 2017.
• Li Zhang, Kamlesh Mistry, Ming Jiang, Siew Chin Neoh, Mohammed Alamgir Hossain, Adaptive facial point detection and emotion recognition for a humanoid robot, Computer Vision and Image Understanding 140 (2015) 93-114.
• Kamlesh Mistry, Jyoti Jasekar, Biju Issac, and Li Zhang, Extended LBP based Facial Expression Recognition System for Adaptive AI Agent Behaviour, 2018 International Joint Conference on Neural Networks (IJCNN), 2018.
