Towards automated recognition of facial expressions in animal models

Gaddi Blumrosen, David Hawellek, Bijan Pesaran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2810-2819
Number of pages10
Volume2018-January
ISBN (Electronic)9781538610343
DOIs
StatePublished - Jan 19 2018
Event16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 - Venice, Italy
Duration: Oct 22 2017Oct 29 2017

Other

Other16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
CountryItaly
CityVenice
Period10/22/1710/29/17

Fingerprint

Animals
Video recording
Image registration
Physiology
Glossaries
Clustering algorithms
Decoding
Muscle
Primates

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Blumrosen, G., Hawellek, D., & Pesaran, B. (2018). Towards automated recognition of facial expressions in animal models. In Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017 (Vol. 2018-January, pp. 2810-2819). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2017.332

Towards automated recognition of facial expressions in animal models. / Blumrosen, Gaddi; Hawellek, David; Pesaran, Bijan.

Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 2810-2819.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Blumrosen, G, Hawellek, D & Pesaran, B 2018, Towards automated recognition of facial expressions in animal models. in Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 2810-2819, 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017, Venice, Italy, 10/22/17. https://doi.org/10.1109/ICCVW.2017.332
Blumrosen G, Hawellek D, Pesaran B. Towards automated recognition of facial expressions in animal models. In Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 2810-2819 https://doi.org/10.1109/ICCVW.2017.332
Blumrosen, Gaddi ; Hawellek, David ; Pesaran, Bijan. / Towards automated recognition of facial expressions in animal models. Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 2810-2819
@inproceedings{4261f121c67e46db9e2ee851503905b6,
title = "Towards automated recognition of facial expressions in animal models",
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.",
author = "Gaddi Blumrosen and David Hawellek and Bijan Pesaran",
year = "2018",
month = "1",
day = "19",
doi = "10.1109/ICCVW.2017.332",
language = "English (US)",
volume = "2018-January",
pages = "2810--2819",
booktitle = "Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Towards automated recognition of facial expressions in animal models

AU - Blumrosen, Gaddi

AU - Hawellek, David

AU - Pesaran, Bijan

PY - 2018/1/19

Y1 - 2018/1/19

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85046272479&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85046272479&partnerID=8YFLogxK

U2 - 10.1109/ICCVW.2017.332

DO - 10.1109/ICCVW.2017.332

M3 - Conference contribution

VL - 2018-January

SP - 2810

EP - 2819

BT - Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -