We propose a method of face recognition that can consistently identify every face angle, assuming it is used in open spaces such as a normal room. We obtain the learning images not from an ideal world but from the real world, where users can move around freely with no constraints. We then automatically classify the face images that vary according to the user's position and posture by self-organization (unsupervised learning), and create a discrimination circuit using only the best face images for the recognition task. We show that the recognition rate for images with various facial angles in the real world can be improved by automatic classification through self-organization.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic face classifications by self-organization for face recognition


    Beteiligte:
    Sato, Y. (Autor:in) / Yoda, I. (Autor:in) / Sakaue, K. (Autor:in)


    Erscheinungsdatum :

    2003-01-01


    Format / Umfang :

    533530 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Automatic Face Classifications by Self-Organization for Face Recognition

    Sato, Y. / Yoda, I. / Sakaue, K. et al. | British Library Conference Proceedings | 2003


    Automatic Seat Adjustment using Face Recognition

    Vamsi, Malneedi / Soman, K.P. / Guruvayurappan, K. | IEEE | 2020


    Automatic face authentication with self compensation

    Lin, T. H. / Shih, W. P. | British Library Online Contents | 2008



    Learning and Caricaturing the Face Space Using Self-Organization and Hebbian Learning for Face Processing

    Pujol, A. / Wechsler, H. / Villanueva, J. et al. | British Library Conference Proceedings | 2001