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Moving Object Detection Based on Kirsch Operator Combined with Optical Flow

机译:基于柯尔希算子和光流的运动目标检测

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The detection of moving object is important in many tasks, such as video surveillance and moving object tracking. Although there are some methods for the moving object detection, it is still a challenging area. In this paper, a new method which combines the Kirsch operator with the Optical Flow method (KOF) is proposed. On the one hand, the Kirsch operator is used to compute the contour of the objects in the video. On the other hand, the Optical Flow method is adopted to establish the motion vector field for the video sequence. Then the Otsu method is implemented after the Optical Flow method in order to distinguish the moving object and the background clearly. Finally the contour information fuses the information of motion vector field to label the moving objects in the video sequences. The experiment results prove that the proposed method is effective for the moving objects detection.
机译:运动对象的检测在许多任务中都很重要,例如视频监视和运动对象跟踪。尽管有一些检测运动物体的方法,但这仍然是一个充满挑战的领域。本文提出了一种将Kirsch算子与光流法(KOF)相结合的新方法。一方面,使用Kirsch运算符来计算视频中对象的轮廓。另一方面,采用光流方法来建立视频序列的运动矢量场。然后在光学流方法之后实施Otsu方法,以便清楚地区分运动对象和背景。最后,轮廓信息融合了运动矢量场的信息,以标记视频序列中的运动对象。实验结果证明了该方法对运动目标的检测是有效的。

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