Extended LBP based Facial Expression Recognition System for Adaptive AI Agent Behaviour

Mistry, Kamlesh, Jasekar, Joyti, Issac, Biju and Zhang, Li (2018) Extended LBP based Facial Expression Recognition System for Adaptive AI Agent Behaviour. In: IEEE World Congress on Computational Intelligence, 8-13 July 2018, Rio de Janeiro.

IJCNN_Mistry_et_al_accepted_manuscript.pdf - Accepted Version

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Automatic facial expression recognition is widely used for various applications such as health care, surveillance and human-robot interaction. In this paper, we present a novel system which employs automatic facial emotion recognition technique for adaptive AI agent behaviour. The proposed system is equipped with kirsch operator based local binary patterns for feature extraction and diverse classifiers for emotion recognition. First, we nominate a novel variant of the local binary pattern (LBP) for feature extraction to deal with illumination changes, scaling and rotation variations. The features extracted are then used as input to the classifier for recognizing seven emotions. The detected emotion is then used to enhance the behaviour selection of the artificial intelligence (AI) agents in a shooter game. The proposed system is evaluated with multiple facial expression datasets and outperformed other state-of-the-art models by a significant margin.

Item Type: Conference or Workshop Item (Paper)
Subjects: G700 Artificial Intelligence
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 01 Oct 2018 08:00
Last Modified: 01 Aug 2021 09:33
URI: http://nrl.northumbria.ac.uk/id/eprint/35952

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