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- W2162868193 abstract "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" @default.
- W2162868193 created "2016-06-24" @default.
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- W2162868193 date "2006-12-01" @default.
- W2162868193 modified "2023-09-26" @default.
- W2162868193 title "Reliable Detection of Overtaking Vehicles Using Robust Information Fusion" @default.
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- W2162868193 doi "https://doi.org/10.1109/tits.2006.883936" @default.
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