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http://bura.brunel.ac.uk/handle/2438/9730
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jan, A | - |
dc.contributor.author | Meng, H | - |
dc.contributor.author | Gaus, YFA | - |
dc.contributor.author | Zhang, F | - |
dc.contributor.author | Turabzadeh, S | - |
dc.coverage.spatial | Orlando, FL, USA | - |
dc.coverage.spatial | Orlando, FL, USA | - |
dc.coverage.spatial | Orlando, FL, USA | - |
dc.coverage.spatial | Orlando, FL, USA | - |
dc.date.accessioned | 2015-01-14T09:34:52Z | - |
dc.date.available | 2014-11-07 | - |
dc.date.available | 2015-01-14T09:34:52Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14): 73 - 80, (2014) | en_US |
dc.identifier.isbn | 978-1-4503-3119-7 | - |
dc.identifier.uri | http://dl.acm.org/citation.cfm?doid=2661806.2661812 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/9730 | - |
dc.description.abstract | Depression is a state of low mood and aversion to activity that can affect a person's thoughts, behaviour, feelings and sense of well-being. In such a low mood, both the facial expression and voice appear different from the ones in normal states. In this paper, an automatic system is proposed to predict the scales of Beck Depression Inventory from naturalistic facial expression of the patients with depression. Firstly, features are extracted from corresponding video and audio signals to represent characteristics of facial and vocal expression under depression. Secondly, dynamic features generation method is proposed in the extracted video feature space based on the idea of Motion History Histogram (MHH) for 2-D video motion extraction. Thirdly, Partial Least Squares (PLS) and Linear regression are applied to learn the relationship between the dynamic features and depression scales using training data, and then to predict the depression scale for unseen ones. Finally, decision level fusion was done for combining predictions from both video and audio modalities. The proposed approach is evaluated on the AVEC2014 dataset and the experimental results demonstrate its effectiveness. | en_US |
dc.description.sponsorship | The work by Asim Jan was supported by School of Engineering & Design/Thomas Gerald Gray PGR Scholarship. The work by Hongying Meng and Saeed Turabzadeh was partially funded by the award of the Brunel Research Initiative and Enterprise Fund (BRIEF). The work by Yona Falinie Binti Abd Gaus was supported by Majlis Amanah Rakyat (MARA) Scholarship. | en_US |
dc.format.extent | 73 - 80 (8) | - |
dc.format.extent | 73 - 80 (8) | - |
dc.format.extent | 73 - 80 (8) | - |
dc.format.extent | 73 - 80 (8) | - |
dc.language.iso | en | en_US |
dc.publisher | ACM | en_US |
dc.source | The 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
dc.source | The 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
dc.source | The 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
dc.source | The 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
dc.subject | Affective computing | en_US |
dc.subject | Depression recognition | en_US |
dc.subject | Beck depression | en_US |
dc.subject | Inventory | en_US |
dc.subject | Facial expression | en_US |
dc.subject | Challenge | en_US |
dc.title | Automatic depression scale prediction using facial expression dynamics and regression | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | http://dx.doi.org/10.1145/2661806.2661812 | - |
dc.relation.isPartOf | Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
dc.relation.isPartOf | Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
dc.relation.isPartOf | Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
dc.relation.isPartOf | Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge (AVEC14) | - |
pubs.finish-date | 2014-11-07 | - |
pubs.finish-date | 2014-11-07 | - |
pubs.finish-date | 2014-11-07 | - |
pubs.finish-date | 2014-11-07 | - |
pubs.place-of-publication | ACM New York, NY, USA | - |
pubs.publication-status | Published | - |
pubs.publication-status | Published | - |
pubs.publication-status | Published | - |
pubs.publication-status | Published | - |
pubs.start-date | 2014-11-07 | - |
pubs.start-date | 2014-11-07 | - |
pubs.start-date | 2014-11-07 | - |
pubs.start-date | 2014-11-07 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Electronic and Computer Engineering | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Electronic and Computer Engineering/Electronic and Computer Engineering | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme/Institute of Environmental, Health and Societies | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme/Institute of Environmental, Health and Societies/Biomedical Engineering and Healthcare Technologies | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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