Increasing driving safety with a multiple vehicle detection and tracking system using ongoing vehicle shadow information

Bureu Aytekin*, Erdinç Altuǧ

*Corresponding author for this work

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

29 Citations (Scopus)

Abstract

This paper proposes a vehicle detection and tracking system based on processing monochrome images captured by a single camera. The work has mainly been focused on detecting and tracking vehicles in daylight conditions, viewed from inside a vehicle. Unlike previous work, this approach uses vehicle shadow clues and vehicle edge information to obtain cost effective and fast estimation. The proposed method includes road area finding which has been implemented by a lane detection algorithm to avoid false detections of vehicles caused by the distraction of background objects. Assuming that lanes are successfully detected, vehicle presence inside the road area is hypothesized by using "shadow" as a cue. Hypothesized vehicle locations are verified using vertical edges. After extracting vehicles, the algorithm effectively tracks them using a Kalman filter based tracking algorithm. A vehicle has been instrumented with various sensors for the experiments. Several sequences from real traffic situations have been tested, obtaining highly accurate multiple vehicle detections. Tracking information is used to estimate time-to-collision (TTC) and waru the driver for a possible collision.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Pages3650-3656
Number of pages7
DOIs
Publication statusPublished - 2010
Event2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey
Duration: 10 Oct 201013 Oct 2010

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Conference

Conference2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Country/TerritoryTurkey
CityIstanbul
Period10/10/1013/10/10

Keywords

  • Collision warning
  • Computer vision
  • Intelligent vehicles
  • Vehicle detection
  • Vehicle tracking

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