BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Distinguishing between genuine and posed smiles

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Publication date
    2019-04-18
    Author
    Ugail, Hassan
    Aldahoud, Ahmad A.A.
    Keyword
    Smile analysis
    Genuine smiles
    Posed smiles
    Smile weight distribution
    Peer-Reviewed
    Yes
    Open Access status
    closedAccess
    
    Metadata
    Show full item record
    Abstract
    This chapter presents an application of computational smile analysis framework discussed earlier. Here we discuss how one could utilise a computational algorithm to distinguish between genuine and posed smiles. We utilise aspects of the computational framework discussed in Chap. 2 to process and analyse the smile expression looking for clues to determine the genuineness of it. Equally, we discuss how the exact distribution of a smile across the face, especially the distinction in the weight distribution between a genuine and a posed smile can be achieved.
    URI
    http://hdl.handle.net/10454/19011
    Version
    No full-text in the repository
    Citation
    Ugail H and Aldahoud AAA (2019) Distinguishing between genuine and posed smiles. In: Computational Techniques for Human Smile Analysis. SpringerBriefs in Computer Science. Springer, Cham. 23-33.
    Link to publisher’s version
    https://doi.org/10.1007/978-3-030-15381-6_3
    Type
    Book chapter
    Collections
    Engineering and Informatics Publications

    entitlement

     

    Related items

    Showing items related by title, author, creator and subject.

    • Thumbnail

      A genuine smile is indeed in the eyes – The computer aided non-invasive analysis of the exact weight distribution of human smiles across the face

      Ugail, Hassan; Al-dahoud, Ahmad (2019-10)
      Understanding the detailed differences between posed and spontaneous smiles is an important topic with a range of applications such as in human-computer interaction, automatic facial emotion analysis and in awareness systems. During the past decade or so, there have been very promising solutions for accurate automatic recognition and detailed facial emotion analysis. To this end, many methods and techniques have been proposed for distinguishing between spontaneous and posed smiles. Our aim here is to go beyond the present state of the art in this field. Hence, in this work, we are concerned with understanding the exact distribution of a smile – both spontaneous and posed – across the face. To do this, we utilise a lightweight computational framework which we have developed to analyse the dynamics of human facial expressions. We utilise this framework to undertake a detailed study of the smile expression. Based on computing the optical flow across the face – especially across key parts of the face such as the mouth, the cheeks and around the eyes – we are able to accurately map the dynamic weight distribution of the smile expression. To validate our computational model, we utilise two publicly available datasets, namely the CK + dataset in which the subjects express posed smiles and the MUG dataset in which the subjects express genuine smiles. Our results not only confirm what already exists in the literature – i.e. that the spontaneous genuine smile is truly in the eyes – but it also gives further insight into the exact distribution of the smile across the face.
    • Thumbnail

      The biometric characteristics of a smile

      Ugail, Hassan; Aldahoud, Ahmad (2019-04-18)
      Facial expressions have been studied looking for its diagnostic capabilities in mental health and clues for longevity, gender and other such personality traits. The use of facial expressions, especially the expression of smile, as a biometric has not been looked into great detail. However, research shows that a person can be identified from their behavioural traits including their emotional expressions. In this Chapter, we discuss a novel computational biometric model which can be derived from the smile expression. We discuss how the temporal components of a smile can be utilised to show that similarities in the smile exist for an individual and it can be enabled to create a tool which can be utilised as a biometric.
    • Thumbnail

      Computational Techniques for Human Smile Analysis

      Ugail, Hassan; Al-dahoud, Ahmad (2019-04-17)
      How many times have you smiled today? How many times have you frowned today? Ever thought of being in a state of self-consciousness to be able to relate your own mood with your facial emotional expressions? Perhaps with our present-day busy lives, we may not consider these as crucial questions. However, as researchers uncover more and more about the human emotional landscape they are learning the importance of understanding our emotions.
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.