• DocumentCode
    1768810
  • Title

    Implementation details of mid-level vision on the Embedded Vision Engine (EVE)

  • Author

    Kamath, Sanmati ; Dabral, Shashank ; Sankaran, Jagadeesh ; Valentine, Brian ; Kisacanin, Branislav

  • Author_Institution
    Texas Instrum. Inc., Dallas, TX, USA
  • fYear
    2014
  • fDate
    1-5 June 2014
  • Firstpage
    1283
  • Lastpage
    1287
  • Abstract
    In this paper we introduce the Embedded Vision Engine (EVE), a novel vision accelerator designed to complement digital signal processors on low- and mid-level vision algorithms. We illustrate EVE´s performance on three important mid-level vision functions, the Hough transform for circles, integral image and calculating the Rotation invariant Binary Robust Independent Elementary Feature (RBRIEF) descriptor. EVE can execute these functions 4 times faster than the state-of-the-art digital signal processor. With other vision functions accelerated 3-12X, the acceleration of these popular vision functions contribute to the application level speed up of 5x on common automotive vision applications. This demonstrates that EVE, while working at powers comparable to the power of a DSP core, can deliver significant boost in performance.
  • Keywords
    automobiles; computer vision; digital signal processing chips; embedded systems; feature extraction; traffic engineering computing; DSP core; EVE; Hough transform; RBRIEF; automotive vision applications; digital signal processors; embedded vision engine; low-level vision algorithms; mid-level vision algorithms; midlevel vision; rotation invariant binary robust independent elementary feature descriptor; vision accelerator; Algorithm design and analysis; Automotive engineering; Digital signal processing; Histograms; Signal processing algorithms; Transforms; Vectors; Embedded Programming; Vector SIMD Processing; Vision Processing;
  • 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.2014.6865377
  • Filename
    6865377