• DocumentCode
    497996
  • Title

    A 22.8GOPS 2.83mW neuro-fuzzy Object Detection Engine for fast multi-object recognition

  • Author

    Kim, Minsu ; Kim, Joo-Young ; Lee, Seungjin ; Oh, Jinwook ; Yoo, Hoi-Jun

  • Author_Institution
    Department of EECS, KAIST, Yuseong, Daejeon, Republic of Korea
  • fYear
    2009
  • fDate
    16-18 June 2009
  • Firstpage
    260
  • Lastpage
    261
  • Abstract
    A neuro-fuzzy Object Detection Engine (ODE) is proposed as the pre-processing accelerator of multi-object recognition processor to reduce the computational complexity. It performs a fast and robust neuro-fuzzy object detection algorithm with Motion Estimator (ME) and Visual Attention Engine (VAE) within 1ms. The mixed mode implementation achieves 22.9GOPS 2.83mW ODE, and reduces the area by 59% and power consumption by 44%. The ODE can increase the frame rate by 2.09x and reduce power consumption by 38% of the multi-object recognition processor.
  • Keywords
    Adaptive systems; Analog-digital conversion; Circuits; Decision making; Energy consumption; Engines; Motion estimation; Object detection; Object recognition; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    VLSI Circuits, 2009 Symposium on
  • Conference_Location
    Kyoto, Japan
  • Print_ISBN
    978-1-4244-3307-0
  • Electronic_ISBN
    978-4-86348-001-8
  • Type

    conf

  • Filename
    5205353
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=497996