• DocumentCode
    2963212
  • Title

    Design of high-performance pedestrian and vehicle detection circuit using Haar-like features

  • Author

    Soojin Kim ; Sangkyun Park ; Seonyoung Lee ; Seungsang Park ; Kyeongsoon Cho

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Hankuk Univ. of Foreign Studies, Yongin, South Korea
  • fYear
    2012
  • fDate
    19-22 Nov. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper describes the design of high-performance pedestrian and vehicle detection circuit using Haar-like features for intelligent vehicle application. The proposed circuit uses a sliding window for every image frame in order to extract Haar-like features and to detect pedestrians and vehicles. A total of 200 Haar-like features per sliding window are extracted from Haar-like feature extraction circuit and the extracted features are provided to AdaBoost classifier circuit. In order to increase the processing speed, the proposed circuit adopts the parallel architecture and it can process two sliding windows at the same time. We described the proposed high-performance pedestrian and vehicle detection circuit using Verilog HDL and synthesized the gate-level circuit using 130nm standard cell library. The synthesized circuit consists of 1,388,260 gates and its maximum operating frequency is 203MHz. Since the proposed circuit processes about 47.8 640×480 image frames per second, it can be used to provide the real-time pedestrian and vehicles detection for intelligent vehicle application.
  • Keywords
    Haar transforms; automated highways; feature extraction; hardware description languages; image classification; learning (artificial intelligence); object detection; parallel architectures; pedestrians; AdaBoost classifier circuit; Haar-like feature extraction circuit; Verilog HDL; gate-level circuit; high-performance pedestrian detection circuit; image frame; intelligent vehicle application; parallel architecture; size 130 nm; sliding window; standard cell library; vehicle detection circuit; Data mining; Feature extraction; Intelligent vehicles; Random access memory; Real-time systems; Vehicle detection; Vehicles; AdaBoost classification; Haar-like feature; Intelligent vehicel application; Pedestiran and vehicle detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2012 - 2012 IEEE Region 10 Conference
  • Conference_Location
    Cebu
  • ISSN
    2159-3442
  • Print_ISBN
    978-1-4673-4823-2
  • Electronic_ISBN
    2159-3442
  • Type

    conf

  • DOI
    10.1109/TENCON.2012.6412165
  • Filename
    6412165