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An advanced method for road course estimation is presented. It is based on the state-of-the-art Kalman filter lane detection and allows for a robust sensor-based estimation of road courses in great distances. Only the parameters for the road course are estimated which results in a reduced parameter space and therewith more robustness. Instead of laterally displaced single feature points tangential...
Various image processing techniques and geometric models have been applied in vision based lane detection subsystems of intelligent vehicles and Advanced Driver Assistance Systems (ADAS). However, challenging conditions such as strong shadows, occlusions, eroded markings, high curvatures are ongoing issues in this topic. In this paper, a novel lane extraction method based on symmetrical local threshold...
As traffic surveillance technologies continue to grow worldwide, vehicle detection, counting and tracking are becoming increasing important. This paper proposes a real-time multi-vehicle detection and tracking approach. Lane marker detection is carried out for vehicle counting on each lane. It also helps remove the foreground noise and shadow. Instead of tracking the entire vehicle blob, vehicle sub-feature...
In the near future automatic systems able to detect the traffic situation and to understand driver behavior and intent will probably become vehicle tools important for improving driver safety. Therefore, robust video processing techniques able to cope with difficult environmental road condition such as luminosity changes, dynamic and cluttered background, etc. are necessary for these applications...
Robust and reliable lane detection is an important issue for driver assistance systems and self-guided systems. Input images acquired from a camera on moving vehicle need to be processed for lane and vehicular traffic detection. We propose an algorithm that uses a chain code detector for detecting lanes and detects vehicles using the horizontal lines formed by the vehicles at the edge of the images...
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