• DocumentCode
    1768197
  • Title

    An Embedded Vision Engine (EVE) for automotive vision processing

  • Author

    Mandal, Dipan Kumar ; Sankaran, Jagadeesh ; Gupta, Arpan ; Castille, Kyle ; Gondkar, Shraddha ; Kamath, Sanmati ; Sundar, Pooja ; Phipps, Alan

  • Author_Institution
    Texas Instrum., Bangalore, India
  • fYear
    2014
  • fDate
    1-5 June 2014
  • Firstpage
    49
  • Lastpage
    52
  • Abstract
    This paper introduces Embedded Vision Engine (EVE) - a fully programmable, specialized vector processor architecture aimed at solving challenging Computer Vision applications encountered in Advanced Driver Assistance Systems (ADAS). The paper outlines the complexity of automotive vision applications, establishes why specialized architecture (like EVE) is needed and outlines the EVE architecture, its components and programming model. We present comparative benchmarks and provide an overview of many carefully crafted features of EVE for power management, inter processor communication, functional safety and software debug that helps in building a scalable, area-power efficient System-on-Chip (SoC) solutions for the cost, power and safety sensitive automotive vision space.
  • Keywords
    computer vision; system-on-chip; traffic engineering computing; ADAS; EVE architecture; advanced driver assistance system; area-power efficient SoC; automotive vision processing; computer vision; embedded vision engine; functional safety; interprocessor communication; power management; software debug; system-on-chip; vector processor architecture; Automotive engineering; Buffer storage; Computer architecture; Digital signal processing; Engines; Safety; Vectors; ADAS; Automotive Vision; Computer Vision; Processor Architecture; SIMD processor; Vector Processor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (ISCAS), 2014 IEEE International Symposium on
  • Conference_Location
    Melbourne VIC
  • Print_ISBN
    978-1-4799-3431-7
  • Type

    conf

  • DOI
    10.1109/ISCAS.2014.6865062
  • Filename
    6865062