Smart city applications are using extensively artificial intelligence for decision-making. Among the fields of application are facial recognition and intrusion detection. The subject is old, but processing techniques and hardware are constantly evolving. This paper will review the most widely known practices and apply them to a smart parking and intrusion detection system using the “JetsonNano” board. Nowadays, quality assurance for machine learning systems is becoming increasingly important. This article focuses on detecting bugs in implementing two classical face recognition algorithms: Eigenface (EF) and Local binary pattern histogram (LBPH). We tested the efficiency of our system using metamorphic testing depending on many factors: weather conditions, pixel noise, and distortion.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Metamorphic Testing for Edge Real-Time Face Recognition and Intrusion Detection Solution


    Contributors:


    Publication date :

    2022-09-01


    Size :

    615259 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Robust real-time face detection

    Viola, P. / Jones, M. | IEEE | 2001


    Robust Real-Time Face Detection

    Viola, P. / Jones, M. / IEEE | British Library Conference Proceedings | 2001


    Robust Real-Time Face Detection

    Viola, P. / Jones, M. J. | British Library Online Contents | 2004


    Testing face recognition systems

    Robertson, G. / Craw, I. | British Library Online Contents | 1994