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A Vehicle Tracing Approach Based on Video and Road Network

机译:基于视频和道路网络的车辆跟踪方法

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Route backtracking has been applied in many fields, especially in tracing criminal cars. However, because of weak light, shading or shelter, plate numbers are unable to be recognized and the vehicle cannot be traced. So, this paper put forwards a route backtracking method based on video data and road network. the method get routes information by means of vehicles features extraction and matching method with time and spatial constraints. Time constraints include time records in each video and time range that car cost on every road, and spatial constraints include connectivity and topology of roads. Meanwhile, there are also vehicle constraints, such as vehicle's outline, color, type and plate number. and this paper uses Mean Shift algorithm to extract and match the candidate vehicles and target vehicle. Finally, an experiment is put forward to prove the availability and efficiency of the method.
机译:路由回溯已应用于许多领域,特别是在追踪犯罪车上。 但是,由于光线,阴影或遮蔽薄,不能识别板号,并且车辆无法跟踪。 因此,本文提出了一种基于视频数据和道路网络的路由回溯方法。 该方法通过车辆获取路线信息,具有时间和空间约束的特征提取和匹配方法。 时间限制包括每台视频和时间范围内的时间记录,以及汽车成本在每条道路上以及空间约束包括道路的连接和拓扑。 同时,还有车辆限制,例如车辆的轮廓,颜色,类型和板号。 本文使用平均转换算法提取并匹配候选车辆和目标车辆。 最后,提出了一个实验来证明方法的可用性和效率。

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