Description: 基于opencv的混合高斯背景模型，用对运动目标的背景提取，可保存背景
-Opencv-based mixture Gaussian background model with the moving target of the background extraction, background can be saved
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Author:hao |
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Description: background substraction using mixture of gaussian model.the algoritm writen in c++ using open cv lib Platform: |
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Author:amilahhhh |
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Description: 实现混合高斯背景建模，对给定图像序列进行背景建模.内置的参数可以自行修改，以适用不同的应用需求。-mixture of gaussian，it will help you to construct the background model of series frames Platform: |
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Author:徐浩然 |
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Description: 混合高斯背景模型相关经典英文论文EI论文-Mixture Gaussian background model classic English papers related to EI papers Platform: |
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Author:贾子 |
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Description: 混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.-The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving
object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of
RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed
uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system.
These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid-
based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis
to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed.
Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels
but also have a better robustness. Platform: |
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Description: 内含visual C++和MATLAB代码，利用高斯呼喝模型进行背景建模，自适应确定高斯分量的个数，由Z.Zivkovic开发，相关文章是 Improved adaptive Gausian mixture model for background subtraction-Containing visual C++ and MATLAB code, the use of Gaussian background modeling feeding model, adaptive determine the number of Gaussian components, developed by Z.Zivkovic related article Improved adaptive Gausian mixture model for background subtraction Platform: |
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Author:huang |
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Description: Focusing on the failure under the condition of target blocking, the similarity between
target color and background color for the Camshift algorithm, an improved algorithm
based on Camshift algorithm is proposed. Gaussian mixture model is used to
determine the tracking area fast and accurately because it is not sensitive to the external
conditions such as light and shadow. Platform: |
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Author:bouch |
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Description: 本文以k-means算法为背景，引入信息熵相关知识，从而实现全自动分割图像。然而在利用混合高斯模型对图像进行数据分析时，会发生一定的过拟合现象，导致我们得不到预期的聚类数目。本文设计合理的合并准则，令模型简化，有效地消除过拟合现象，使得最后得到的聚类数目与预期符合。，设计合理的准则改进了图像的全自动分割方法，使得分割结果更加优化(In this paper, k-means algorithm is used as the background, and information entropy related knowledge is introduced to realize full-automatic image segmentation. However, when the Gaussian mixture model is used to analyze the image data, there will be some over-fitting phenomenon, resulting in that we cannot get the expected number of clusters. In this paper, a reasonable merging criterion is designed to simplify the model and effectively eliminate the over-fitting phenomenon, so that the final clustering number is in line with the expectation. A reasonable criterion is designed to improve the automatic image segmentation method and make the segmentation result more optimized.) Platform: |
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Author:xiaoxiaofish |
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