Symmetrical judgement area reduction and ECoHOG feature descriptor for pedestrian detection

Hirokatsu Kataoka, Yoshimitsu Aoki, Yasuhiro Matsui

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this study, a method to detect pedestrians using an in-vehicle camera is presented. We improved the technology in detecting pedestrians with highly accurate images using a monocular camera. We were able to predict pedestrians' activities by monitoring them, and we developed an algorithm to recognise pedestrians and their movements more accurately. For the feature descriptor, we found that an Extended Co-occurrence Histogram of Oriented Gradients (ECoHOG) was the best in decreasing both the undetectable and the excessive detectable ratio. Thus, the use of the new method by images captured on the real road was validated.

Original languageEnglish
Pages (from-to)48-60
Number of pages13
JournalInternational Journal of Vehicle Safety
Volume6
Issue number1
DOIs
Publication statusPublished - 2012 Aug 1

    Fingerprint

Keywords

  • Active safety
  • ECoHOG
  • Extended co-occurrence histogram of oriented gradients
  • Monocular camera
  • Pedestrian detection
  • Symmetrical judgement area reduction

ASJC Scopus subject areas

  • Automotive Engineering

Cite this