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A Monte-Carlo-based Algorithm for Background Generation

机译:基于蒙特卡洛的背景生成算法

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In this study, a Monte-Carlo-based algorithm, named CRF, was developed for generating background images from a video sequence. This algorithm is a variant of the Teknomo-Fernandez (TF) algorithm, an efficient background generation algorithm that also incorporates the Monte-Carlo concept and applies simple logical bit operations. Two different configurations of CRF were implemented, i.e. CRF9,2 and CRF81,1. A brute force algorithm that generates the ground truth using modal pixel bit values was also developed in order to analyze the empirical performances of the TF algorithm and the 2 CRF configurations. Experiments on some colored video tests show that the CRF configurations outperform the TF algorithm in terms of accuracy. However, the TF algorithm remains more efficient in terms of processing time.
机译:在这项研究中,开发了一种基于蒙特卡洛的算法,称为CRF,用于从视频序列生成背景图像。该算法是Teknomo-Fernandez(TF)算法的一种变体,它是一种高效的背景生成算法,还结合了Monte-Carlo概念并应用了简单的逻辑位运算。实现了两种不同的CRF配置,即CRF9,2和CRF81,1。为了分析TF算法和​​2种CRF配置的经验性能,还开发了使用模态像素位值生成地面真相的蛮力算法。一些彩色视频测试的实验表明,在准确性方面,CRF配置优于TF算法。但是,TF算法在处理时间方面仍然更加有效。

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