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Adaptive Search Window for Object Tracking in the Crowds using Undecimated Wavelet Packet Features

机译:使用未抽取小波包特征的人群中对象跟踪的自适应搜索窗口

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In this paper, we propose an adaptive object tracking algorithm in crowded scenes. The amplitudes of of Undecimated Wavelet Packet Tree coefficients for some selected pixels at the object border are used to create a Feature Vector (FV) corresponding to that pixel. The algorithm uses these FVs to track the pixels of small square blocks located at the vicinity of the object boundary. The search window is adapted through the use of texture information of the scene by finding the direction and speed of the object motion. Experimental results show a good object tracking performance in crowds that include object translation, rotation, scaling and partial occlusion.
机译:在本文中,我们提出了一种在拥挤场景中的自适应目标跟踪算法。在对象边界处某些选定像素的未抽取小波包树系数的幅度用于创建与该像素相对应的特征向量(FV)。该算法使用这些FV来跟踪位于对象边界附近的小方块的像素。通过找到物体运动的方向和速度,通过使用场景的纹理信息来调整搜索窗口。实验结果表明,在包括对象平移,旋转,缩放和部分遮挡的人群中,对象跟踪性能良好。

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