Title :
Robust Road Modeling and Tracking Using Condensation
Author :
Wang, Yan ; Bai, Li ; Fairhurst, Michael
Author_Institution :
Sch. of Comput. Sci., Univ. of Nottingham, Nottingham
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.
Keywords :
computer vision; image segmentation; object detection; parameter estimation; particle filtering (numerical methods); road traffic; tracking; traffic engineering computing; video signal processing; computer vision; condensation particle filter; contextual information; parameter estimation; real-time video-based navigation; road boundary line segment; road detection; road modeling; road tracking; vanishing point detection; Computer vision; condensation filter; road detection and tracking;
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2008.2006733