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An Effective Background Reconstruction Method for Video Objects Detection

机译:用于视频对象检测的有效背景重构方法

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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:背景减法是检测移动物体的重要方法,有效的背景重建是背景减法的关键。 基于图像系列中的高频出现的像素平均值是背景点,像素强度分类(PIC)算法可以精确地重建背景。 本文提出了一种基于PIC算法的新型背景估计方法。 通过归一化,所选图像序列的像素的定量统计量,量化范围延伸用于重建背景。 基于由改进的PIC算法重建的背景,我们构建具有OpenCV的移动物体检测系统。 实验结果表明,本文提出的方法可以快速重建背景图像,可以成功地从视频序列中提取移动对象。

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