A multiple-lane vehicle tracking method for forward collision warning system applications

Yuan Fu Li, Chia Chi Tsai, Yi Ting Lai, Jiun-In  Guo

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

3 Scopus citations

Abstract

This paper proposes a vehicle tracking method for the Forward Collision Warning System (FCWS). The proposed method applies vehicle detection and feature tracking to each frame in the videos to enhance the detection accuracy and increase the stability of vehicle localization. The proposed method can be applied to three-lane FCWS which includes left, main, and right lanes. The performance of the proposed three-lane FCWS can achieve 720×480 video@183 fps in average when realized in PC with Intel Core i7 processor with average detection accuracy of 94.05% at daytime and 86.90% at night. The proposed method is also implemented on Freescale i.MX6 embedded platform with a USB webcam to capture the video. Under the D1 (720×480) resolution, the performance of the proposed 3-lane FCWS can achieve 29 fps.

Original languageEnglish
Title of host publicationProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1061-1064
Number of pages4
ISBN (Electronic)9781538615423
DOIs
StatePublished - 5 Feb 2018
Event9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia
Duration: 12 Dec 201715 Dec 2017

Publication series

NameProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Volume2018-February

Conference

Conference9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Country/TerritoryMalaysia
CityKuala Lumpur
Period12/12/1715/12/17

Fingerprint

Dive into the research topics of 'A multiple-lane vehicle tracking method for forward collision warning system applications'. Together they form a unique fingerprint.

Cite this