File(s) under permanent embargo
Deep hybrid spatiotemporal networks for continuous pain intensity estimation
conference contribution
posted on 2019-01-01, 00:00 authored by S Thuseethan, Sutharshan RajasegararSutharshan Rajasegarar, John YearwoodJohn YearwoodHumans use rich facial expressions to indicate unpleasant emotions, such as pain. Automatic pain intensity estimation is useful in a variety of applications in social and medical domains. However, the existing pain intensity estimation approaches are limited to either classifying the discrete intensity levels in pain or estimating the continuous pain intensities without considering the key-frame. The first approach suffers from abnormal fluctuations while estimating the pain intensity levels. Further, continuous pain estimation approaches suffer from low prediction capabilities. Hence, in this paper, we propose a deep hybrid network based approach to automatically estimate the continuous pain intensities by incorporating spatiotemporal information. Our approach consists of two key components, namely key-frame analyser and temporal analyser. We use one conventional and two recurrent convolutional neural networks to design key-frame and temporal analysers, respectively. Further, the evaluation on a benchmark dataset shows that our model can estimate the continuous emotions better than existing state-of-the-art methods.
History
Event
Asia-Pacific Neural Network Society. International Conference (26th : 2019 : Sydney, N.S.W.)Volume
11955Series
Asia-Pacific Neural Network Society International ConferencePagination
449 - 461Publisher
SpringerLocation
Sydney, N.S.W.Place of publication
Cham, SwitzerlandPublisher DOI
Start date
2019-12-12End date
2019-12-15ISSN
0302-9743eISSN
1611-3349ISBN-13
9783030367176Language
engPublication classification
E1 Full written paper - refereedEditor/Contributor(s)
T Gedeon, K Wong, M LeeTitle of proceedings
APNNS 2019 : Proceedings of the 26th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society 2019Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC