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• W2024495812 abstract "We propose a multi-layer, real-time vehicle detection and tracking system using stereo vision, multi-view AdaBoost detectors, and optical flow. By adopting a ground plane estimate extracted from stereo information, we generate a sparse set of hypotheses and apply trained AdaBoost classifiers in addition to fast disparity histogramming, for Hypothesis Verification (HV) purposes. Our tracking system employs one Kalman filter per detected vehicle and motion vectors from optical flow, as a means to increase its robustness. An acceptable detection rate with few false positives is obtained at 25 fps with generic hardware." @default.
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• W2024495812 date "2011-10-01" @default.
• W2024495812 modified "2023-09-23" @default.
• W2024495812 title "Real-time vehicle detection and tracking using stereo vision and multi-view AdaBoost" @default.
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• W2024495812 doi "https://doi.org/10.1109/itsc.2011.6082972" @default.
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