A low-cost pedestrian detection system with a single optical camera

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

This paper presents a low-cost solution for pedestrian detection using a single optical video camera on a moving vehicle. Since only one optical camera can collect just a little original information, our system scan two sequential frames to get both appearance and motion information. We use zoom image and slide window techniques to select the objective region, apply a cascaded classifier combined with statistical learning and SVM to recognize human body, adopt zoom-scale to estimate the distance from a pedestrian and develop a Distance Transform algorithm to forecast his/her orientation. This system is suitable for detecting pedestrians in the range of 0.3-20 meters in the city traffic with the speed under 50 km/h. The test with videos of real city traffic indicates that our system has got acceptable detecting rate and processing speed.

Original languageEnglish
Title of host publicationProceedings of the World Congress on Intelligent Control and Automation (WCICA)
Pages8759-8763
Number of pages5
DOIs
StatePublished - 2006
Externally publishedYes
Event6th World Congress on Intelligent Control and Automation, WCICA 2006 - Dalian, China
Duration: 21 Jun 200623 Jun 2006

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)
Volume2

Conference

Conference6th World Congress on Intelligent Control and Automation, WCICA 2006
Country/TerritoryChina
CityDalian
Period21/06/0623/06/06

Keywords

  • Cascaded classifier
  • Decomposed SVM
  • Distance transform algorithm
  • Pedestrian detection system
  • Statistical learning

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