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Video inpainting model for camera motion based on improved background subtraction method

机译:基于改进背景减法的摄像机运动视频修复模型

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Motion object detection has been widely used in traffic monitoring and target tracking fields. In order to solve the difficulty of building a model of the background and improving the accuracy of the update rate in the background subtraction, a new detection moving object method combining the surf algorithm and the background subtraction is proposed in this paper. Firstly, according to the continuity of motion, motion regions are labeled and filled in; Secondly, the image mosaic by surf algorithm is conducted to obtain the image with the whole background, then the whole background image mosaic is used to obtain the frame image with the whole background; Finally, frame difference method is used to obtain the foreground object, and then a morphology is processed. The experiment has not only achieved higher accuracy which is improved by about 8%∼10%, but also got lower error which is reduced by 3.5%∼4.0%. In a word, the algorithm has better robustness.
机译:运动目标检测已广泛应用于交通监控和目标跟踪领域。为了解决背景减法建立背景模型和提高更新率准确性的困难,提出了一种新的结合surf算法和背景减法的运动目标检测方法。首先,根据运动的连续性,对运动区域进行标记和填充;其次,通过surf算法进行图像拼接,得到整个背景图像,然后使用整个背景图像拼接得到整个背景图像。最后,采用帧差法获得前景物体,然后进行形态学处理。实验不仅达到了较高的精度,提高了约8%〜10%,而且降低了误差,降低了3.5%〜4.0%。总之,该算法具有更好的鲁棒性。

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