Front vehicle tracking using scene analysis

Kai-Tai Song*, Chih Chieh Yang

*Corresponding author for this work

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

9 Scopus citations

Abstract

This paper presents a design and implementation of a real-time visual tracking system for vehicle safety applications. A novel feature-based vehicle tracking algorithm is proposed. This algorithm can automatically detect and track multiple moving objects, including cars and motorcycles, ahead of the tracking vehicle. Combined with the concept of focus of expansion (FOE) and scene analysis, the developed system can segment features of moving objects from moving background and provide a collision warning in real time. The proposed algorithm is realized using a CMOS image sensor and Nios embedded processor architecture. The constructed stand-alone visual tracking system has been validated in actual road tests. Experimental results show that the proposed system successfully tracks front vehicles and provides information of collision warning in urban artery with speed around 60 km/hr both at night and day times.

Original languageEnglish
Title of host publicationIEEE International Conference on Mechatronics and Automation, ICMA 2005
Pages1323-1328
Number of pages6
DOIs
StatePublished - 17 Nov 2005
EventIEEE International Conference on Mechatronics and Automation, ICMA 2005 - Niagara Falls, ON, Canada
Duration: 29 Jul 20051 Aug 2005

Publication series

NameIEEE International Conference on Mechatronics and Automation, ICMA 2005

Conference

ConferenceIEEE International Conference on Mechatronics and Automation, ICMA 2005
CountryCanada
CityNiagara Falls, ON
Period29/07/051/08/05

Keywords

  • Advanced safety vehicles
  • Embedded system
  • Image processing
  • Vehicle tracking
  • Visual tracking

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