A comparison of the performance of humans and computational models in the classification of facial expression

2.50
Hdl Handle:
http://hdl.handle.net/10547/279219
Title:
A comparison of the performance of humans and computational models in the classification of facial expression
Authors:
Shenoy, Aruna; Anthony, Sue; Frank, Ray; Davey, Neil
Abstract:
Recognizing expressions are a key part of human social interaction, and processing of facial expression information is largely automatic for humans, but it is a non-trivial task for a computational system. In the first part of the experiment, we develop computational models capable of differentiating between two human facial expressions. We perform pre-processing by Gabor filters and dimensionality reduction using the methods: Principal Component Analysis, and Curvilinear Component Analysis. Subsequently the faces are classified using a Support Vector Machines. We also asked human subjects to classify these images and then we compared the performance of the humans and the computational models. The main result is that for the Gabor pre-processed model, the probability that an individual face was classified in the given class by the computational model is inversely proportional to the reaction time for the human subjects.
Citation:
Shenoy, A., Anthony, S., Frank, R.J. and Davey, N. (2009) 'A comparison of the performance of humans and computational models in the classification of facial expression', International conference on Cognitive Modelling, Manchester, UK.
Journal:
Cognitive Science Society
Issue Date:
2009
URI:
http://hdl.handle.net/10547/279219
Additional Links:
http://sideshow.psyc.bbk.ac.uk/rcooper/iccm2009/proceedings/index.html
Type:
Conference papers, meetings and proceedings
Language:
en
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorShenoy, Arunaen_GB
dc.contributor.authorAnthony, Sueen_GB
dc.contributor.authorFrank, Rayen_GB
dc.contributor.authorDavey, Neilen_GB
dc.date.accessioned2013-04-07T19:42:09Z-
dc.date.available2013-04-07T19:42:09Z-
dc.date.issued2009-
dc.identifier.citationShenoy, A., Anthony, S., Frank, R.J. and Davey, N. (2009) 'A comparison of the performance of humans and computational models in the classification of facial expression', International conference on Cognitive Modelling, Manchester, UK.en_GB
dc.identifier.urihttp://hdl.handle.net/10547/279219-
dc.description.abstractRecognizing expressions are a key part of human social interaction, and processing of facial expression information is largely automatic for humans, but it is a non-trivial task for a computational system. In the first part of the experiment, we develop computational models capable of differentiating between two human facial expressions. We perform pre-processing by Gabor filters and dimensionality reduction using the methods: Principal Component Analysis, and Curvilinear Component Analysis. Subsequently the faces are classified using a Support Vector Machines. We also asked human subjects to classify these images and then we compared the performance of the humans and the computational models. The main result is that for the Gabor pre-processed model, the probability that an individual face was classified in the given class by the computational model is inversely proportional to the reaction time for the human subjects.en_GB
dc.language.isoenen
dc.relation.urlhttp://sideshow.psyc.bbk.ac.uk/rcooper/iccm2009/proceedings/index.htmlen_GB
dc.subjectfacial expressionsen_GB
dc.subjectimage analysisen_GB
dc.titleA comparison of the performance of humans and computational models in the classification of facial expressionen
dc.typeConference papers, meetings and proceedingsen
dc.identifier.journalCognitive Science Societyen_GB
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