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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Advanced Particle Filtering for Airborne Vehicle Tracking in Urban Areas
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Advanced Particle Filtering for Airborne Vehicle Tracking in Urban Areas

机译：先进的微粒过滤技术，可用于城市地区的空中车辆追踪

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Individual vehicle trajectories from airborne image sequences provide valuable input for traffic analysis. The main characteristics of the employed camera system are given by a pixel resolution between 4.5 and 12 cm and a frame rate of 2 Hz. Three problems of particle filtering for vehicle tracking are addressed as follows. First, an adaptive motion model is presented, which controls the spreading of the particle cloud in the search space of each vehicle. Second, a spatiotemporal particle guiding approach includes the context of adjacent vehicles into the tracker to increase the stability of the tracker. Third, appearance changes of the vehicles are handled by a template update strategy. An adaptive likelihood function is introduced to balance a flexible and a strict observation model. The qualitative and quantitative evaluation on the image sequences taken from an airplane and an unmanned aerial vehicle demonstrate the improved robustness of the tracker.
机译：来自机载图像序列的单个车辆轨迹为交通分析提供了有价值的输入。所用相机系统的主要特征是像素分辨率在4.5至12 cm之间，帧频为2 Hz。解决了用于车辆跟踪的粒子滤波的三个问题，如下所述。首先，提出了一种自适应运动模型，该模型控制粒子云在每辆车的搜索空间中的扩散。其次，时空粒子引导方法将邻近车辆的环境纳入跟踪器，以增加跟踪器的稳定性。第三，车辆的外观变化由模板更新策略处理。引入自适应似然函数以平衡灵活和严格的观察模型。对从飞机和无人驾驶飞机拍摄的图像序列进行的定性和定量评估表明，跟踪器具有更高的鲁棒性。

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