Facial emotion recognition with a reduced feature set for video game and metaverse avatars

Darren Bellenger, Minsi Chen, Zhijie Xu

Research output: Contribution to journalArticlepeer-review


This paper presents a novel real-time facial feature extraction algorithm, producing a small feature set, suitable for implementing emotion recognition with online game and metaverse avatars. The algorithm aims to reduce data transmission and storage requirements, hurdles in the adoption of emotion recognition in these mediums. The early results presented show a facial emotion recognition accuracy of up to 92% on one benchmark dataset, with an overall accuracy of 77.2% across a wide range of datasets, demonstrating the early promise of the research.
Original languageEnglish
Article numbere2230
Number of pages16
JournalComputer Animation and Virtual Worlds
Issue number2
Publication statusPublished - 1 Mar 2024

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