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A Low-cost Occlusion Handling Using a Novel Feature In Congested Traffic Images

机译:在拥挤的交通图像中使用新颖功能进行低成本遮挡处理

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Occlusion detection is critical for robust and reliable vision-based systems for traffic flow analysis. In this paper we discuss novel occlusion detection approach. The goal of this algorithm is to detect vehicles in congested traffic scenes with occlusion handling. Also we proposed a new proper feature for vehicle detection to avoid the merging of two or more objects into one and to improve the accuracy of object localization. This feature is strong shadow which exists under any vehicle. Many sequences of real images including noisy images, cluttered, and images containing remarkable shadows and occlusions, taken from both scenes of outdoor highways and city roads, have been taken for evaluating our method.
机译:闭塞检测对于交通流量分析的基于鲁棒和可靠的视觉系统至关重要。在本文中,我们讨论了新型闭塞检测方法。该算法的目标是通过遮挡处理来检测拥挤的交通场景中的车辆。此外,我们提出了一种新的车辆检测特征,以避免将两个或多个物体合并到一个并提高对象本地化的准确性。此功能是任何车辆都存在的强烈阴影。已经采取了从户外高速公路和城市道路的场景中占用的嘈杂图像,杂乱的图像,杂乱和闭塞的许多真实图像的序列,包括从户外高速公路和城市道路的场景中进行评估。

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