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Detection and segmentation of moving objects in complex scenes

机译:复杂场景中运动物体的检测与分割

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In this paper, we address the difficult task of detecting and segmenting foreground moving objects in complex scenes. The sequences we consider exhibit highly dynamic backgrounds, illumination changes and low contrasts, and can have been shot by a moving camera. Three main steps compose the proposed method. First, a set of moving points is selected within a sub-grid of image pixels. A multi-cue descriptor is associated to each of these points. Clusters of points are then formed using a variable bandwidth mean shift technique with automatic bandwidth selection. Finally, segmentation of the object associated to a given cluster is performed using graph cuts. Experiments and comparisons to other motion detection methods on challenging sequences demonstrate the performance of the proposed method for video analysis in complex scenes.
机译:在本文中,我们解决了在复杂场景中检测和分割前景移动物体的艰巨任务。我们认为这些序列具有高动态背景,照明变化和低对比度,并且可以由移动的相机拍摄。三个主要步骤构成了所提出的方法。首先,在图像像素的子网格内选择一组移动点。多提示描述符与这些点中的每一个关联。然后使用具有自动带宽选择功能的可变带宽均值偏移技术形成点的群集。最后,使用图割对与给定群集相关联的对象进行分割。实验和与其他运动检测方法的比较具有挑战性的序列证明了该方法在复杂场景中进行视频分析的性能。

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