Video analysis for improving transportation safety. obstacles and collision detection applied to railways and roads

Hui Wang, Xiaoquan Zhang, Lorenzo Damiani, Pietro Giribone, Roberto Revetria*, Giacomo Ronchetti

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Obstacles detection systems are essential to achieve a higher level of safety on railways. Such systems should have the ability to contribute to the development of automated guided trains. Even though some laser equipments have been used to detect obstacles, short detection distance and low accuracy on curve zones make them not the best solution. In this paper, computer vision combined with prior knowledge is used to develop an innovative approach. A function to find the starting point of the rails is proposed. After that bottom-up adaptive windows are created to focus on the region of interest and ignore the background. The whole system can run in real time thanks to its linear complexity. It performs well in different conditions and it can work both on online and offline recorded video.

Original languageEnglish
Title of host publicationProceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017
EditorsOscar Castillo, S. I. Ao, Craig Douglas, David Dagan Feng, A. M. Korsunsky
PublisherNewswood Limited
Pages909-915
Number of pages7
Volume2
ISBN (Electronic)9789881404770
Publication statusPublished - 01 Apr 2017
Externally publishedYes
Event2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017 - Hong Kong, Hong Kong
Duration: 15 Mar 201717 Mar 2017

Publication series

NameLecture Notes in Engineering and Computer Science
Volume2228
ISSN (Print)2078-0958
ISSN (Electronic)2078-0966

Conference

Conference2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017
Country/TerritoryHong Kong
CityHong Kong
Period15/03/201717/03/2017

Keywords

  • Computer vision
  • Obstacles detection
  • Prior Knowledge
  • Transportation
  • Video Forensic

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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