Abstract
Facial expressions play a significant role in the expression of emotional states, such as fear, surprise, and happiness in humans and other animals. The current systems for recognizing animal facial expression model in Non-human primates (NHPs) are currently limited to manual decoding of the facial muscles and observations, which is biased, time-consuming and requires a long training process and certification. The main objective of this work is to establish a computational framework for facial recognition systems for automatic recognition NHP facial expressions from standard video recordings with minimal assumptions. The suggested technology consists of: 1)a tailored facial image registration for NHPs; 2)a two-layers unsupervised clustering algorithm that forms an ordered dictionary of facial images for different facial segments; 3)extract dynamical temporal-spectral features;, and recognize dynamic facial expressions. The feasibility of the methods was verified using video recordings of an NHP under various behavioral conditions, recognizing typical NHP facial expressions in the wild. The results were compared to three human experts, and show an agreement of more than 82%. This work is the first attempt for efficient automatic recognition of facial expressions in NHPs using minimal assumptions about the physiology of facial expressions.
Original language | English |
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Title of host publication | Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2810-2819 |
Number of pages | 10 |
ISBN (Electronic) | 9781538610343 |
DOIs | |
State | Published - 1 Jul 2017 |
Externally published | Yes |
Event | 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 - Venice, Italy Duration: 22 Oct 2017 → 29 Oct 2017 |
Publication series
Name | Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017 |
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Volume | 2018-January |
Conference
Conference | 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 |
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Country/Territory | Italy |
City | Venice |
Period | 22/10/17 → 29/10/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Funding
6. Acknowledgments We would like to thank, Marsela Rubiano, Breonna Ferrentino, and Nia Boles for their efforts in tagging the lower facial expression video clips, Eshkol Fund Mr. Avraham and Mrs. Rivka Blumrosen encouragement (GB), Leopoldina Fellowship Programme Grant (LPDS/LPDR 2012-09) (DH), and an Award from the Simons Collaboration on the Global Brain (BP).
Funders | Funder number |
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Simons Collaboration on the Global Brain | |
BP |