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An Effective Background Reconstruction Method for Video Objects Detection

机译:一种有效的视频目标检测背景重建方法

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The background subtraction is an important method to detect the moving objects, and effective background reconstruction is the key for the background subtraction. Based on the idea that the pixel average appearing with high frequency in an image series is the background points, the pixel intensity classification (PIC) algorithm can reconstruct background accurately. In this paper, a new background estimation method based on the PIC algorithm is proposed. Through normalization, quantitative statistic, quantization range extension of the pixels of the chosen image sequence is used to reconstruct the background. Based on the background reconstructed by the improved PIC algorithm, we build a moving object detection system with OpenCV. The experiments results show that the method proposed in this paper can reconstruct the background image quickly and can extract the moving objects from the video sequence successfully.
机译:背景扣除是检测运动物体的重要方法,有效的背景重建是背景扣除的关键。基于图像序列中高频出现的像素平均值是背景点的思想,像素强度分类(PIC)算法可以准确地重建背景。提出了一种基于PIC算法的背景估计新方法。通过归一化,所选图像序列的像素的定量统计,量化范围扩展可用于重建背景。在改进PIC算法重构背景的基础上,建立了OpenCV运动目标检测系统。实验结果表明,本文提出的方法能够快速重建背景图像,并能成功地从视频序列中提取运动对象。

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