Extended feature descriptor and vehicle motion model with tracking-by-detection for pedestrian active safety

Hirokatsu Kataoka, Kimimasa Tamura, Kenji Iwata, Yutaka Satoh, Yasuhiro Matsui, Yoshimitsu Aoki

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The percentage of pedestrian deaths in traffic accidents is on the rise in Japan. In recent years, there have been calls for measures to be introduced to protect vulnerable road users such as pedestrians and cyclists. In this study, a method to detect and track pedestrians using an in-vehicle camera is presented. We improve the technology of detecting pedestrians by using the highly accurate images obtained with a monocular camera. In the detection step, we employ ECoHOG as the feature descriptor; it accumulates the integrated gradient intensities. In the tracking step, we apply an effective motion model using optical flow and the proposed feature descriptor ECoHOG in a tracking-by-detection framework. These techniques were verified using images captured on real roads.

Original languageEnglish
Pages (from-to)296-304
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE97-D
Issue number2
DOIs
Publication statusPublished - 2014

Keywords

  • ECoHOG
  • Particle filter
  • Pedestrian active safety
  • Tracking-by-detection
  • Vehicle motion model

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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