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Space-Time Multi-Resolution Banded Graph-Cut for Fast Segmentation

机译:用于快速分割的时空多分辨率带状图剪切

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Applying real-time segmentation is a major issue when processing every frame of image sequences. In this paper, we propose a modification of the well known graph-cut algorithm to improve speed for discrete segmentation. Our algorithm yields real-time segmentation, using graph-cut, by performing a single cut on an image with regions of different resolutions, combining space-time pyramids and narrow bands. This is especially suitable for image sequences, as segment borders in one image are refined in the next image. The fast computation time allows one to use information contained in every image frame of an input image stream at 20 Hz, on a standard PC. The algorithm is applied to traffic scenes, using a monocular camera installed in a moving vehicle. Our results show the segmentation of moving objects with similar results to standard graph-cut, but with improved speed.
机译:在处理图像序列的每一帧时,应用实时分割是一个主要问题。在本文中,我们提出了对众所周知的图割算法的改进,以提高离散分割的速度。我们的算法通过对具有不同分辨率区域的图像执行单次切割,并结合时空金字塔和窄带,使用图形切割来进行实时分割。这尤其适用于图像序列,因为一个图像中的段边界在下一个图像中得到了细化。快速的计算时间允许在标准PC上以20 Hz的频率使用输入图像流的每个图像帧中包含的信息。使用安装在行驶中的车辆中的单眼相机,将该算法应用于交通场景。我们的结果显示了对运动对象的分割,其结果与标准图形切割相似,但速度有所提高。

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