CogEmoNet: A Cognitive-Feature-Augmented Driver Emotion Recognition Model for Smart Cockpit
文献类型：期刊论文
| 作者 | Li, Wenbo7 ; Zeng, Guanzhong7; Zhang, Juncheng7; Xu, Yan6; Xing, Yang1; Zhou, Rui5; Guo, Gang7; Shen, Yu4; Cao, Dongpu3; Wang, Fei-Yue2
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| 刊名 | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
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| 出版日期 | 2021-11-29 |
| 页码 | 12 |
| 关键词 | Emotion recognition Feature extraction Cognitive processes Face recognition Task analysis Information processing Convolutional neural networks Affective computing driver emotion facial expression human-machine interaction (HMI) smart cockpit |
| ISSN号 | 2329-924X |
| DOI | 10.1109/TCSS.2021.3127935 |
| 通讯作者 | Guo, Gang(guogang@cqu.edu.cn) |
| 英文摘要 | Driver's emotion recognition is vital to improving driving safety, comfort, and acceptance of intelligent vehicles. This article presents a cognitive-feature-augmented driver emotion detection method that is based on emotional cognitive process theory and deep networks. Different from the traditional methods, both the driver's facial expression and cognitive process characteristics (age, gender, and driving age) were used as the inputs of the proposed model. Convolutional techniques were adopted to construct the model for driver's emotion detection simultaneously considering the driver's facial expression and cognitive process characteristics. A driver's emotion data collection was carried out to validate the performance of the proposed method. The collected dataset consists of 40 drivers' frontal facial videos, their cognitive process characteristics, and self-reported assessments of driver emotions. Another two deep networks were also used to compare recognition performance. The results prove that the proposed method can achieve well detection results for different databases on the discrete emotion model and dimensional emotion model, respectively. |
| WOS关键词 | IDENTIFICATION ; NETWORK |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000727916600001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.ia.ac.cn/handle/173211/46770]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 通讯作者 | Guo, Gang |
| 作者单位 | 1.Cranfield Univ, Dept Aerosp Transport & Mfg, Cranfield MK43 0AL, Beds, England 2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China 3.Univ Waterloo, Dept Mech & Mechatron Engn, Waterloo, ON N2L 3G1, Canada 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 5.Waytous Inc, Dept Res & Dev, Shenzhen, Peoples R China 6.Univ Sci & Technol Beijing, Dept Mech Engn, Beijing 100083, Peoples R China 7.Chongqing Univ, Coll Mech & Vehicle Engn, Chongqing 400044, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Wenbo,Zeng, Guanzhong,Zhang, Juncheng,et al. CogEmoNet: A Cognitive-Feature-Augmented Driver Emotion Recognition Model for Smart Cockpit[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2021:12. |
| APA | Li, Wenbo.,Zeng, Guanzhong.,Zhang, Juncheng.,Xu, Yan.,Xing, Yang.,...&Wang, Fei-Yue.(2021).CogEmoNet: A Cognitive-Feature-Augmented Driver Emotion Recognition Model for Smart Cockpit.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,12. |
| MLA | Li, Wenbo,et al."CogEmoNet: A Cognitive-Feature-Augmented Driver Emotion Recognition Model for Smart Cockpit".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2021):12. |
入库方式： OAI收割
来源：自动化研究所
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