BROWSE
Detail
Conference Paper
Deep Emotion Change Detection for Human-robot Interaction
Cited - time in 
Share 
Share
- Authors
- ByungOk Han, Ho Won Kim, Jang-Hee Yoo
- Issue Date
- 2020-10
- Citation
- International Conference on Intelligent Robots and Systems (IROS) 2020, pp.12142-12145
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Emotion change detection via facial expression information is an important clue to non-verbal communication that can uncover emotional context. In a human-robot interaction scenario, figuring out the timing of emotion changes using facial expression information from an user has three advantages on: 1) providing a start point to obtain timeconsistent multi-modal information, 2) reducing search space in time series, and 3) producing feedback information to improve the scenario. In this regard, we introduce an initial investigation to an automatic emotion change detection framework in the field of human-robot interaction. To tackle this issue, we propose a novel method of deep emotion change detection for inferencing emotion status and detecting multiple points of emotion changes. Incorporating these ideas, we provide evaluation methods to validate the framework and the baseline performance of our approach.
- KSP Keywords
- Detection Framework, Emotion change detection, Evaluation method, Facial expression, Feedback information, Human robot interaction(HRI), Modal information, Multi-modal, Non-Verbal Communication, Search Space, Time series