Avatar Emotion Recognition using Non-verbal Communication

dc.contributor.authorBazargani, Jalal Safarien_US
dc.contributor.authorSadeghi-Niaraki, Abolghasemen_US
dc.contributor.authorChoi, Soo-Mien_US
dc.contributor.editorChaine, Raphaëlleen_US
dc.contributor.editorDeng, Zhigangen_US
dc.contributor.editorKim, Min H.en_US
dc.date.accessioned2023-10-09T07:42:53Z
dc.date.available2023-10-09T07:42:53Z
dc.date.issued2023
dc.description.abstractAmong the sources of information about emotions, body movements, recognized as ''kinesics'' in non-verbal communication, have received limited attention. This research gap suggests the need to investigate suitable body movement-based approaches for making communication in virtual environments more realistic. Therefore, this study proposes an automated emotion recognition approach suitable for use in virtual environments. This study consists of two pipelines for emotion recognition. For the first pipeline, i.e., upper-body keypoint-based recognition, the HEROES video dataset was employed to train a bidirectional long short-term memory model using upper-body keypoints capable of predicting four discrete emotions: boredom, disgust, happiness, and interest, achieving an accuracy of 84%. For the second pipeline, i.e., wrist-movement-based recognition, a random forest model was trained based on 17 features computed from acceleration data of wrist movements along each axis. The model achieved an accuracy of 63% in distinguishing three discrete emotions: sadness, neutrality, and happiness. The findings suggest that the proposed approach is a noticeable step toward automated emotion recognition, without using any additional sensors other than the head mounted display (HMD).en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationPacific Graphics Short Papers and Posters
dc.identifier.doi10.2312/pg.20231277
dc.identifier.isbn978-3-03868-234-9
dc.identifier.pages103-104
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/pg.20231277
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pg20231277
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing -> Human computer interaction (HCI)
dc.subjectHuman centered computing
dc.subjectHuman computer interaction (HCI)
dc.titleAvatar Emotion Recognition using Non-verbal Communicationen_US
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