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Study the improved CAMSHIFT algorithm to detect the moving object in fisheye image

机译:研究改进的CAMSHIFT算法检测鱼眼图像中的运动物体

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Fisheye lens has been applied more and more in the digital video surveillance system because of large field of view, but the fisheye image is distortion greatly which restricted its further application. According to the characteristics distortion of circular fisheye image, this paper studied an improved Camshift object detection algorithm and applied to the moving object tracking and detection in the fisheye surveillance system. Firstly, the principle of the Meanshift algorithm was discussed, and then the Camshift algorithm which based on the Meanshift algorithm was studied. Lastly, the improved algorithm of Camshift was designed which based on the Camshift algorithm and the characteristics of the fisheye image, and validity of the algorithm by calculation. The experiment results shows that the improved Camshift algorithm can detecting and tracking the moving object in fisheye image stabilization and effective, whether it is in the middle position or on the edge with compression seriously. It has a very good application in the intelligent and nothing blind-zone surveillance system.
机译:鱼眼镜头由于其较大的视场范围而在数字视频监控系统中得到越来越多的应用,但是鱼眼镜头的图像畸变严重,限制了其进一步的应用。针对圆形鱼眼图像的特征畸变,研究了一种改进的Camshift目标检测算法,并将其应用于鱼眼监控系统中的运动目标跟踪与检测。首先讨论了Meanshift算法的原理,然后研究了基于Meanshift算法的Camshift算法。最后,基于Camshift算法和鱼眼图像的特点,通过计算得出算法的有效性,设计了改进的Camshift算法。实验结果表明,改进的Camshift算法可以有效地检测和跟踪鱼眼图像中的运动物体,无论该运动物体处于中间位置还是受到严重压缩的边缘,均有效。它在智能无盲区监控系统中有很好的应用。

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