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A moving object extraction algorithm based on the modified codebook model

机译:基于改进码本模型的运动目标提取算法

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摘要

The extraction of moving targets in complex background scenes is an important part of computer vision applications. The basic method to extract the interest object is to build time series models of pixels. However, these models are often complex and also consume memories. In order to reduce the computational complexity and to streamline computing time, an improved model base on the conventional codebook model is proposed in this paper. Our improved background model is constructed with codebooks consists of codewords. The codewords are encoded based on a box model corresponding to the change scopes of pixels. At the pixel modeling stage, by using blocks surrounding the pixel area to initialize the codebook, and adjusting the position of access codewords, the modeling time is reduced. Our experiments show that the improved codebook algorithm proposed has the higher robustness and accuracy than the conventional codebook algorithm.
机译:提取复杂背景场景中的运动目标是计算机视觉应用程序的重要组成部分。提取兴趣对象的基本方法是建立像素的时间序列模型。但是,这些模型通常很复杂,并且还会占用内存。为了降低计算复杂度并简化计算时间,本文提出了一种基于传统码本模型的改进模型。我们改进的背景模型是由包含代码字的代码本构成的。基于对应于像素的变化范围的盒模型对码字进行编码。在像素建模阶段,通过使用像素区域周围的块来初始化代码簿,并调整访问代码字的位置,可以减少建模时间。我们的实验表明,提出的改进码本算法比常规码本算法具有更高的鲁棒性和准确性。

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