A vision system for monitoring intermodal freight trains

Avinash Kumar, Narendra Ahuja, John M. Hart, U. K. Visesh, P. J. Narayanan, C. V. Jawahar

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

Abstract

We describe the design and implementation of a vision based Intermodal Train Monitoring System(ITMS) for extracting various features like length of gaps in an intermodal(IM) train which can later be used for higher level inferences. An intermodal train is a freight train consisting of two basic types of loads - containers and trailers. Our system first captures the video of an IM train, and applies image processing and machine learning techniques developed in this work to identify the various types of loads as containers and trailers. The whole process relies on a sequence of following tasks - robust background subtraction in each frame of the video, estimation of train velocity, creation of mosaic of the whole train from the video and classification of train loads into containers and trailers. Finally, the length of gaps between the loads of the IM train is estimated and is used to analyze the aerodynamic efficiency of the loading pattern of the train, which is a critical aspect of freight trains. This paperfocusses on the machine vision aspect of the whole system.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE Workshop on Applications of Computer Vision, WACV 2007
PublisherIEEE Computer Society
Pages24-29
Number of pages6
ISBN (Print)0769527949, 9780769527949
DOIs
StatePublished - 2007
Event7th IEEE Workshop on Applications of Computer Vision, WACV 2007 - Austin, TX, United States
Duration: Feb 21 2007Feb 22 2007

Publication series

NameProceedings - IEEE Workshop on Applications of Computer Vision, WACV 2007

Other

Other7th IEEE Workshop on Applications of Computer Vision, WACV 2007
CountryUnited States
CityAustin, TX
Period2/21/072/22/07

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Software

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