Knowledge Commons of Institute of Automation,CAS
Generalized zero-shot emotion recognition from body gestures | |
Wu, Jinting1,2; Zhang, Yujia1; Sun, Shiying1; Li, Qianzhong1,2; Zhao, Xiaoguang1 | |
发表期刊 | APPLIED INTELLIGENCE |
ISSN | 0924-669X |
2021-11-01 | |
页码 | 19 |
摘要 | In human-human interaction, body language is one of the most important emotional expressions. However, each emotion category contains abundant emotional body gestures, and basic emotions used in most researches are difficult to describe complex and diverse emotional states. It is costly to collect sufficient samples of all emotional expressions, and new emotions or new body gestures that are not included in the training set may appear during testing. To address the above problems, we design a novel mechanism that treats each emotion category as a collection of multiple body gesture categories to make better use of gesture information for emotion recognition. A Generalized Zero-Shot Learning (GZSL) framework is introduced to recognize both seen and unseen body gesture categories with the help of semantic information, and emotion predictions are further provided based on the relationship between gestures and emotions. This framework consists of two branches. The first branch is a Hierarchical Prototype Network (HPN) which learns the prototypes of body gestures and uses them to calculate the emotion attentive prototypes. This branch aims to obtain predictions on samples of the seen gesture categories. The second branch is a Semantic Auto-Encoder (SAE) which utilizes semantic representations to predict samples of unseen gesture categories. Thresholds are further trained to determine which branch result will be used during testing, and the emotion labels are finally obtained from these results. Comprehensive experiments are conducted on an emotion recognition dataset which contains skeleton data of multiple body gestures, and the performance of our framework is superior to both the traditional emotion classifier and state-of-the-art zero-shot learning methods. |
关键词 | Generalized zero-shot learning Emotion recognition Body gesture recognition Prototype learning |
DOI | 10.1007/s10489-021-02927-w |
关键词[WOS] | CLASSIFICATION ; MOVEMENT ; NETWORK |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Project of China[2019YFB1310601] ; National Key R&D Program of China[2017YFC0820203] ; National Natural Science Foundation of China[62103410] |
项目资助者 | National Key Research and Development Project of China ; National Key R&D Program of China ; National Natural Science Foundation of China |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000713535200001 |
出版者 | SPRINGER |
七大方向——子方向分类 | 机器人感知与决策 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/46354 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
通讯作者 | Zhang, Yujia |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wu, Jinting,Zhang, Yujia,Sun, Shiying,et al. Generalized zero-shot emotion recognition from body gestures[J]. APPLIED INTELLIGENCE,2021:19. |
APA | Wu, Jinting,Zhang, Yujia,Sun, Shiying,Li, Qianzhong,&Zhao, Xiaoguang.(2021).Generalized zero-shot emotion recognition from body gestures.APPLIED INTELLIGENCE,19. |
MLA | Wu, Jinting,et al."Generalized zero-shot emotion recognition from body gestures".APPLIED INTELLIGENCE (2021):19. |
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