Abstract
Micro emotions are a unique type of facial expression as they are involuntary and very brief. They usually occur when a person attempts to suppress or hide their emotions. Lasting less than 500 ms, they can be very hard to detect even for the human eye, however, since they reveal a person's true feelings, they are of extreme interest in many fields of study. Most approaches to automatic detection and classification of micro emotions rely on detecting the small residual facial movements. In this paper, we propose to exploit an aspect of the human face which is much harder to subdue, namely, facial color change due to blood flow during expression of emotion. We propose a system that evaluates color change during micro emotion expression and successfully classifies the emotion type. This approach is unique in that it disregards the motion related aspects of the expression, and relies entirely on the facial color. We show that our system improves over movement based approaches.
Original language | English |
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Title of host publication | Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1673-1680 |
Number of pages | 8 |
ISBN (Electronic) | 9781728150239 |
DOIs | |
State | Published - Oct 2019 |
Event | 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 - Seoul, Korea, Republic of Duration: 27 Oct 2019 → 28 Oct 2019 |
Publication series
Name | Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 |
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Conference
Conference | 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 27/10/19 → 28/10/19 |
Bibliographical note
Funding Information:This research was supported by grant no 1455/16 from the Israeli Science Foundation.
Publisher Copyright:
© 2019 IEEE.
Keywords
- Deep learning
- Facial color
- Micro emotion
- Micro expression
ASJC Scopus subject areas
- Computer Science Applications
- Computer Vision and Pattern Recognition