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Object tracking with particle filter in UAV video

机译:在UAV视频中与粒子滤波器的对象跟踪

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Aerial surveillance is a main functionality of UAV, which is realized via video camera. During the operations, the mission assigned targets always are the kinetic objects, such as people or vehicles. Therefore, object tracking is taken as the key techniques for UAV sensor payload. Two difficulties for UAV object tracking are dynamic background and hardly predicting target's motion. To solve the problems, it employed the particle filter in the research. Modeling the target by its characteristics, for instance, color features, it approximates the possibility density of target state with weighting sample sets, and the state vector contains position, motion vector and region parameters. The experiments demonstrate the effectiveness and robustness of the proposed method in UAV video tracking.
机译:空中监测是UAV的主要功能,通过摄像机实现。在业务期间,分配目标的特派团始终是动力对象,例如人员或车辆。因此,将对象跟踪作为UAV传感器有效载荷的关键技术。 UAV对象跟踪的两个困难是动态背景,几乎无法预测目标的运动。为了解决问题,它在研究中使用了粒子过滤器。通过其特性建模目标,例如,颜色特征,它近似于具有加权样本集的目标状态的可能性密度,并且状态向量包含位置,运动矢量和区域参数。实验证明了UAV视频跟踪中提出的方法的有效性和鲁棒性。

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