A Video-Based Facial Behaviour Analysis Approach to Melancholia

Shalini BHATIA, Munawar HAYAT, Michael Breakspear, Gordon Parker, Roland GOECKE

Research output: A Conference proceeding or a Chapter in BookConference contribution

4 Citations (Scopus)

Abstract

Recent years have seen a lot of activity in affective computing for automated analysis of depression. However, no research has so far directly evaluated the performance of facial behavioural analysis methods in classifying different subtypes of depression such as melancholia. The mental state assessment of a mood disorder depends largely on appearance, behaviour, speech, thought, perception, mood and facial affect. Mood and facial affect mainly contribute to distinguishing melancholia from non-melancholia. These are assessed by clinicians, and hence vulnerable to subjective judgement. As a result, clinical assessment alone may not accurately capture the presence or absence of specific disorders such as melancholia, a distressing condition whose presence has important treatment implications. Melancholia is characterised by severe anhedonia and psychomotor disturbance, which can be a mix of motor retardation with periods of superimposed agitation. To the best of our knowledge, this study is the first attempt to perform facial behavioural analysis to disambiguate melancholia from non-melancholia and healthy controls on the basis of facial behavioural characteristics. We report the sensitivity and specificity of classification in depressive subtypes. These results serve as a baseline for more fine-grained depression classification and analysis.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017)
Place of PublicationWashington DC, USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages754-761
Number of pages8
ISBN (Electronic)9781509040230
ISBN (Print)9781509040247
DOIs
Publication statusPublished - 30 May 2017
Event12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) - Washington, DC, USA, Washington, DC, United States
Duration: 30 May 20173 Jun 2017

Publication series

Name2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017)
ISSN (Print)2326-5396

Conference

Conference12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)
CountryUnited States
CityWashington, DC
Period30/05/173/06/17

Fingerprint

Depressive Disorder
Depression
Anhedonia
Speech Perception
Mood Disorders
Sensitivity and Specificity
Research

Cite this

BHATIA, S., HAYAT, M., Breakspear, M., Parker, G., & GOECKE, R. (2017). A Video-Based Facial Behaviour Analysis Approach to Melancholia. In Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017) (pp. 754-761). [7961817] (2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017)). Washington DC, USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/FG.2017.94
BHATIA, Shalini ; HAYAT, Munawar ; Breakspear, Michael ; Parker, Gordon ; GOECKE, Roland. / A Video-Based Facial Behaviour Analysis Approach to Melancholia. Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017). Washington DC, USA : IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 754-761 (2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017)).
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BHATIA, S, HAYAT, M, Breakspear, M, Parker, G & GOECKE, R 2017, A Video-Based Facial Behaviour Analysis Approach to Melancholia. in Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017)., 7961817, 2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017), IEEE, Institute of Electrical and Electronics Engineers, Washington DC, USA, pp. 754-761, 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) , Washington, DC, United States, 30/05/17. https://doi.org/10.1109/FG.2017.94

A Video-Based Facial Behaviour Analysis Approach to Melancholia. / BHATIA, Shalini; HAYAT, Munawar; Breakspear, Michael; Parker, Gordon; GOECKE, Roland.

Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017). Washington DC, USA : IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 754-761 7961817 (2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017)).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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N2 - Recent years have seen a lot of activity in affective computing for automated analysis of depression. However, no research has so far directly evaluated the performance of facial behavioural analysis methods in classifying different subtypes of depression such as melancholia. The mental state assessment of a mood disorder depends largely on appearance, behaviour, speech, thought, perception, mood and facial affect. Mood and facial affect mainly contribute to distinguishing melancholia from non-melancholia. These are assessed by clinicians, and hence vulnerable to subjective judgement. As a result, clinical assessment alone may not accurately capture the presence or absence of specific disorders such as melancholia, a distressing condition whose presence has important treatment implications. Melancholia is characterised by severe anhedonia and psychomotor disturbance, which can be a mix of motor retardation with periods of superimposed agitation. To the best of our knowledge, this study is the first attempt to perform facial behavioural analysis to disambiguate melancholia from non-melancholia and healthy controls on the basis of facial behavioural characteristics. We report the sensitivity and specificity of classification in depressive subtypes. These results serve as a baseline for more fine-grained depression classification and analysis.

AB - Recent years have seen a lot of activity in affective computing for automated analysis of depression. However, no research has so far directly evaluated the performance of facial behavioural analysis methods in classifying different subtypes of depression such as melancholia. The mental state assessment of a mood disorder depends largely on appearance, behaviour, speech, thought, perception, mood and facial affect. Mood and facial affect mainly contribute to distinguishing melancholia from non-melancholia. These are assessed by clinicians, and hence vulnerable to subjective judgement. As a result, clinical assessment alone may not accurately capture the presence or absence of specific disorders such as melancholia, a distressing condition whose presence has important treatment implications. Melancholia is characterised by severe anhedonia and psychomotor disturbance, which can be a mix of motor retardation with periods of superimposed agitation. To the best of our knowledge, this study is the first attempt to perform facial behavioural analysis to disambiguate melancholia from non-melancholia and healthy controls on the basis of facial behavioural characteristics. We report the sensitivity and specificity of classification in depressive subtypes. These results serve as a baseline for more fine-grained depression classification and analysis.

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BHATIA S, HAYAT M, Breakspear M, Parker G, GOECKE R. A Video-Based Facial Behaviour Analysis Approach to Melancholia. In Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017). Washington DC, USA: IEEE, Institute of Electrical and Electronics Engineers. 2017. p. 754-761. 7961817. (2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017)). https://doi.org/10.1109/FG.2017.94