IEICE - Transactions on Information and Systems
Critical motion detection of nearby moving vehicles in a vision-based driver-assistance system
IEEE Transactions on Intelligent Transportation Systems
Analysis of multiresolution-based fusion strategies for a dual infrared system
IEEE Transactions on Intelligent Transportation Systems
Controller for urban intersections based on wireless communications and fuzzy logic
IEEE Transactions on Intelligent Transportation Systems
Intelligent automatic overtaking system using vision for vehicle detection
Expert Systems with Applications: An International Journal
The Adaptive Recommendation Mechanism for Lane-Changing at Safe Distances in Vehicular Environments
Wireless Personal Communications: An International Journal
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Early detection of overtaking vehicles is an important task for vision-based driver assistance systems. Techniques utilizing image motion are likely to suffer from spurious image structures caused by shadows and illumination changes, let alone the aperture problem. To achieve reliable detection of overtaking vehicles, the authors have developed a robust detection method, which integrates dynamic scene modeling, hypothesis testing, and robust information fusion. A robust fusion algorithm, based on variable bandwidth density fusion and multiscale mean shift, is introduced to obtain reliable motion estimation against various image noise. To further reduce detection error, the authors model the dynamics of road scenes and exploit useful constraints induced by the temporal coherence in vehicle overtaking. The proposed solution is integrated into a monocular vision system onboard for obstacle detection. Test results have shown superior performance achieved by the new method