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Conference Paper: Emotion recognition using eye gaze based on shallow cnn with identity mapping

TitleEmotion recognition using eye gaze based on shallow cnn with identity mapping
Authors
Jin, ShanQing, ChunmeiXu, XiangminWang, Yang
KeywordsArousal
Emotion recognition
Eye gaze
Shallow CNN with identity mapping
Valence
Issue Date2020
Citation
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020, v. 11691 LNAI, p. 65-75 How to Cite?
DOI: http://dx.doi.org/10.1007/978-3-030-39431-8_7
AbstractMachine recognition of human emotions has attracted more and more attention for its wide application in recent years. As a spontaneous signal of human behavior, eye gaze is utilized for emotion recognition. Compared with electroencephalogram (EEG) signals, eye gaze data is more available, and it can be used in many practical applications, such as virtual reality (VR). In this paper, a new method of human emotion recognition based on eye gaze is proposed. Firstly, a new set of eye gaze features is proposed which consists of eye gaze sequences, extracted statistical feature sequences and spectral feature sequences. Then, the eye gaze feature set is input into the convolutional layer to extract high-level features. Finally, these high-level features and the eye gaze feature set are combined to complete the mapping of features to human emotions. Experiments on MAHNOB-HCI dataset demonstrate the effectiveness of this method.
Persistent Identifierhttp://hdl.handle.net/10722/363349
ISSN
0302-9743
2023 SCImago Journal Rankings: 0.606

 

DC FieldValueLanguage
dc.contributor.authorJin, Shan-
dc.contributor.authorQing, Chunmei-
dc.contributor.authorXu, Xiangmin-
dc.contributor.authorWang, Yang-
dc.date.accessioned2025-10-10T07:46:12Z-
dc.date.available2025-10-10T07:46:12Z-
dc.date.issued2020-
dc.identifier.citationLecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020, v. 11691 LNAI, p. 65-75-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/363349-
dc.description.abstractMachine recognition of human emotions has attracted more and more attention for its wide application in recent years. As a spontaneous signal of human behavior, eye gaze is utilized for emotion recognition. Compared with electroencephalogram (EEG) signals, eye gaze data is more available, and it can be used in many practical applications, such as virtual reality (VR). In this paper, a new method of human emotion recognition based on eye gaze is proposed. Firstly, a new set of eye gaze features is proposed which consists of eye gaze sequences, extracted statistical feature sequences and spectral feature sequences. Then, the eye gaze feature set is input into the convolutional layer to extract high-level features. Finally, these high-level features and the eye gaze feature set are combined to complete the mapping of features to human emotions. Experiments on MAHNOB-HCI dataset demonstrate the effectiveness of this method.-
dc.languageeng-
dc.relation.ispartofLecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics-
dc.subjectArousal-
dc.subjectEmotion recognition-
dc.subjectEye gaze-
dc.subjectShallow CNN with identity mapping-
dc.subjectValence-
dc.titleEmotion recognition using eye gaze based on shallow cnn with identity mapping-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-030-39431-8_7-
dc.identifier.scopuseid_2-s2.0-85080938035-
dc.identifier.volume11691 LNAI-
dc.identifier.spage65-
dc.identifier.epage75-
dc.identifier.eissn1611-3349-

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