• DocumentCode
    1758722
  • Title

    AMBA bus hardware accelerator IP for Viola-Jones face detection

  • Author

    Acasandrei, Laurentiu ; Barriga, Angel

  • Author_Institution
    CNM, Inst. de Microelectron. de Sevilla, Univ. Sevilla, Sevilla, Spain
  • Volume
    7
  • Issue
    5
  • fYear
    2013
  • fDate
    41518
  • Firstpage
    200
  • Lastpage
    209
  • Abstract
    Face detection is an important aspect for biometrics, video surveillance and human computer interaction. Owing to the complexity of the detection algorithms any biometric system requires a huge amount of computational and memory resources. A direct software-like implementation of any detection algorithm on a low speed, low resource, low power system on chip (SoC) is not feasible. Instead, a software-hardware codesign approach can be used to build hardware accelerators for the most computational consuming parts of the detection algorithms. Therefore the authors propose a compliant advanced microcontroller bus architecture (AMBA) bus hardware IP, a modularised, highly configurable, low power and technology independent core written in an hardware description language (HDL) language. The IP core accelerates Viola-Jones algorithm considered to be one of the most used algorithms for face detection. The hardware accelerator IP is used in an embedded face detection system built around the LEON3 Sparc V8 processor. The authors present the methodology, challenges and performance results for software, hardware and system level design. For the mentioned system the authors have obtained an acceleration factor of 10-12 when using the hardware accelerator in comparison with the software only traditional approach.
  • Keywords
    embedded systems; face recognition; hardware description languages; hardware-software codesign; microprocessor chips; storage management; AMBA bus hardware accelerator IP; HDL language; IP core; LEON3 Sparc V8 processor; Viola-Jones face detection; biometrics; computational resources; direct software implementation; embedded face detection system; human computer interaction; low power SoC; low power system on chip; memory resources; software-hardware codesign approach; system level design; video surveillance;
  • fLanguage
    English
  • Journal_Title
    Computers & Digital Techniques, IET
  • Publisher
    iet
  • ISSN
    1751-8601
  • Type

    jour

  • DOI
    10.1049/iet-cdt.2012.0118
  • Filename
    6584852