Ego-Vehicle Corridors for Vision-Based Driver Assistance
IWCIA '09 Proceedings of the 13th International Workshop on Combinatorial Image Analysis
CyberC3: a prototype cybernetic transportation system for urban applications
IEEE Transactions on Intelligent Transportation Systems
A sensor fusion framework using multiple particle filters for video-based navigation
IEEE Transactions on Intelligent Transportation Systems
Driver's behavior assessment by on-board/off-board video context analysis
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
A novel system for robust lane detection and tracking
Signal Processing
Keeping the vehicle on the road: A survey on on-road lane detection systems
ACM Computing Surveys (CSUR)
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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.