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This paper targets at detecting preceding vehicles in a wide range of distance. We propose an Adaboost-based approach combined with hierarchical image and sub-window scaling schemes. The relationship is investigated among object characteristics, image structures and image scales. A parameter set is developed to easily adjust overall performance, which benefits researchers to establish a vehicle detection...
We present a two-layer night time vehicle detector in this work. At the first layer, vehicle headlight detection is applied to find areas (bounding boxes) where the possible pairs of headlights locate in the image, the Haar feature based AdaBoost framework is then applied to detect the vehicle front. This approach has achieved a very promising performance for vehicle detection at night time. Our results...
In this paper, we firstly describe improved Adaboost algorithm, and then introduce wavelet moment, which has rotation, shift, scale moment invariants and multi-resolution characteristic, and which can not only extract image local feature, but also can extract global feature. so it is more stronger to oppose noise. This paper proposes dynamic pyramid changing idea of detector scale. A cascade classifier...
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