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Robust Road Modeling and Tracking using Condensation

Wang, Yan, Bai, Li, Fairhurst, Michael (2008) Robust Road Modeling and Tracking using Condensation. IEEE Transactions on Intelligent Transportation Systems, 9 (4). pp. 570-579. ISSN 1524-9050. (doi:10.1109/TITS.2008.2006733) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:17526)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/TITS.2008.2006733

Abstract

In this paper, we present a robust road detection and tracking method based on a condensation particle filter for real-time video-based navigation applications. The image is divided into horizontal strips, and vanishing point (VP) detection is performed on each image strip. We propose a method for estimating the density of road boundary line segments in the image so that VP detection in an image strip takes into account the detection results in the neighboring image strips. This use of contextual information for VP detection leads to more accurate detection results. The estimated road parameters are then used to initialize the condensation tracker. Experiments using real road videos demonstrate the robustness of our method to difficult road conditions due to the presence of partial occlusion, shadows and road signs.

Item Type: Article
DOI/Identification number: 10.1109/TITS.2008.2006733
Uncontrolled keywords: Computer vision; condensation filter; road detection and tracking
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Funders: Ordnance Survey (https://ror.org/02xqyv944)
Depositing User: J. Harries
Date Deposited: 25 Mar 2009 15:14 UTC
Last Modified: 12 Jul 2022 10:39 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/17526 (The current URI for this page, for reference purposes)

University of Kent Author Information

Fairhurst, Michael.

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