Face detection is a widely studied topic in computer vision, and advances in algorithms, low cost processing, and CMOS imagers make it practical for embedded consumer applications. As with graphics, the best cost-performance ratio is achieved with dedicated hardware. The challenges of face detection in embedded environments include bandwidth constraints set by low cost memory and a need to find parallelism. Consumer applications need reliability, calling for a hard real-time approach to guarantee that deadlines are met. We present a face detection system for automatic exposure control in a handheld digital camera or camera phone. Contributions include a complexity control scheme to meet hard real-time deadlines, a hardware pipeline design for Haar-like feature calculation, and a system design exploiting several levels of parallelism. The proposed architecture is verified by synthesis to Altera’s low cost Cyclone II FPGA. Simulation results show the algorithm can achieve about 80% detection rate for group portrait pictures.


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    Titel :

    Face detection for automatic exposure control in handheld camera


    Beteiligte:
    Ming Yang, (Autor:in) / Ying Wu, (Autor:in) / Crenshaw, J. (Autor:in) / Augustine, B. (Autor:in) / Mareachen, R. (Autor:in)


    Erscheinungsdatum :

    2006-01-01


    Format / Umfang :

    806736 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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