基于kirsch算子结合光流的运动目标检测

P. Gao, Xiang-yu Sun, Wei Wang
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引用次数: 29

摘要

运动目标的检测在视频监控和运动目标跟踪等任务中具有重要意义。尽管已有一些运动目标检测方法,但这仍然是一个具有挑战性的领域。本文提出了一种将Kirsch算子与光流法(KOF)相结合的方法。一方面,利用Kirsch算子计算视频中物体的轮廓;另一方面,采用光流法建立视频序列的运动向量场。然后在光流法之后实现Otsu法,以便清晰地区分运动物体和背景。最后,轮廓信息融合运动向量场信息,对视频序列中的运动物体进行标记。实验结果证明了该方法对运动目标的检测是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Moving object detection based on kirsch operator combined with Optical Flow
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.
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