View in EDS

User action and facial expression recognition for error detection system in an ambient assisted environment.

Saved in:
Bibliographic Details
Title: User action and facial expression recognition for error detection system in an ambient assisted environment.
Authors: Yaddaden, Yacine1 yacine.yaddaden1@uqac.ca, Adda, Mehdi1,2 mehdi_adda@uqar.ca, Bouzouane, Abdenour1 abdenour_bouzouane@uqac.ca, Gaboury, Sébastien1 sebastien_gaboury@uqac.ca, Bouchard, Bruno1 bruno_bouchard@uqac.ca
Source: Expert Systems with Applications. Dec2018, Vol. 112, p173-189. 17p.
Subjects: Facial expression, Error detection (Information theory), Human-robot interaction, Artificial neural networks, Radio frequency
Abstract: Emotion recognition through facial expressions represents a relevant way to understand and even predict the human behavior. Thus, it has been used in various fields such as human-robot interaction and ambient assistance. Nevertheless, it remains a challenging task since expressed emotions might be affected by different parameters such as ethnic origins, age and so on. In this paper, we introduce an efficient facial expression recognition approach based on a Convolutional Neural Network architecture. Carried experimentation on five benchmark facial expression datasets confirms the efficiency of the proposed approach with recognition rates higher than 95 % . In the context of ambient assistance, we introduced an error detection module using a user action recognition from Radio Frequency IDentification tags placed on various objects of daily living. The experiments performed in a smart environment show a consistent improvement of the error detection module when including facial expression recognition. Indeed, the false positive detection rate is significantly reduced by over 20 % . [ABSTRACT FROM AUTHOR]
Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 131185238
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: User action and facial expression recognition for error detection system in an ambient assisted environment.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Yaddaden%2C+Yacine%22">Yaddaden, Yacine</searchLink><relatesTo>1</relatesTo><i> yacine.yaddaden1@uqac.ca</i><br /><searchLink fieldCode="AR" term="%22Adda%2C+Mehdi%22">Adda, Mehdi</searchLink><relatesTo>1,2</relatesTo><i> mehdi_adda@uqar.ca</i><br /><searchLink fieldCode="AR" term="%22Bouzouane%2C+Abdenour%22">Bouzouane, Abdenour</searchLink><relatesTo>1</relatesTo><i> abdenour_bouzouane@uqac.ca</i><br /><searchLink fieldCode="AR" term="%22Gaboury%2C+Sébastien%22">Gaboury, Sébastien</searchLink><relatesTo>1</relatesTo><i> sebastien_gaboury@uqac.ca</i><br /><searchLink fieldCode="AR" term="%22Bouchard%2C+Bruno%22">Bouchard, Bruno</searchLink><relatesTo>1</relatesTo><i> bruno_bouchard@uqac.ca</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Expert+Systems+with+Applications%22">Expert Systems with Applications</searchLink>. Dec2018, Vol. 112, p173-189. 17p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Facial+expression%22">Facial expression</searchLink><br /><searchLink fieldCode="DE" term="%22Error+detection+%28Information+theory%29%22">Error detection (Information theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Human-robot+interaction%22">Human-robot interaction</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Radio+frequency%22">Radio frequency</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Emotion recognition through facial expressions represents a relevant way to understand and even predict the human behavior. Thus, it has been used in various fields such as human-robot interaction and ambient assistance. Nevertheless, it remains a challenging task since expressed emotions might be affected by different parameters such as ethnic origins, age and so on. In this paper, we introduce an efficient facial expression recognition approach based on a Convolutional Neural Network architecture. Carried experimentation on five benchmark facial expression datasets confirms the efficiency of the proposed approach with recognition rates higher than 95 % . In the context of ambient assistance, we introduced an error detection module using a user action recognition from Radio Frequency IDentification tags placed on various objects of daily living. The experiments performed in a smart environment show a consistent improvement of the error detection module when including facial expression recognition. Indeed, the false positive detection rate is significantly reduced by over 20 % . [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=131185238
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.eswa.2018.06.033
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 173
    Subjects:
      – SubjectFull: Facial expression
        Type: general
      – SubjectFull: Error detection (Information theory)
        Type: general
      – SubjectFull: Human-robot interaction
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Radio frequency
        Type: general
    Titles:
      – TitleFull: User action and facial expression recognition for error detection system in an ambient assisted environment.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yaddaden, Yacine
      – PersonEntity:
          Name:
            NameFull: Adda, Mehdi
      – PersonEntity:
          Name:
            NameFull: Bouzouane, Abdenour
      – PersonEntity:
          Name:
            NameFull: Gaboury, Sébastien
      – PersonEntity:
          Name:
            NameFull: Bouchard, Bruno
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2018
              Type: published
              Y: 2018
          Identifiers:
            – Type: issn-print
              Value: 09574174
          Numbering:
            – Type: volume
              Value: 112
          Titles:
            – TitleFull: Expert Systems with Applications
              Type: main
ResultId 1