In order to overcome the impact of complex illumination environment and head movement, a novel eye state recognition algorithm is proposed in this paper, which is based on feature level fusion. Firstly, Pseudo Zernike feature was found can be used to overcome the impact of head movement and Gabor feature can be used to overcome the impact of illumination changing. Then we got the fusion feature by combining the two normalized features in series and used it in SVM eye state classifier. The experimental results show that the new fusion feature can overcome the challenges of head movement and illumination and reach a high accuracy of 99.8% in eye state recognition.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An eye state recognition algorithm based on feature level fusion


    Beteiligte:
    Tong, Ximing (Autor:in) / Qin, Huabiao (Autor:in) / Zhuo, Linhai (Autor:in)


    Erscheinungsdatum :

    01.06.2017


    Format / Umfang :

    446931 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Feature-Level Fusion Recognition of Space Targets With Composite Micromotion

    Zhang, Yuanpeng / Xie, Yan / Kang, Le et al. | IEEE | 2024


    Feature-level sensor fusion

    Peli, T. Young, M. Knox, R. Ellis, K. K. | British Library Conference Proceedings | 1999



    A Dynamic Gesture Recognition Algorithm based on Feature Fusion from RGB-D Sensor

    Wang, Xia / Chen, Peng / Wu, Man et al. | British Library Conference Proceedings | 2022


    Dual Space Based Face Recognition Using Feature Fusion

    Patra, A. / Das, S. / Visual Information Engineering Network (Institution of Engineering and Technology) | British Library Conference Proceedings | 2006