Description: 减背景算法，基于背景建模的方法获取前景目标，采用高斯混合模型-By the background algorithm, based on background modeling method to get the prospect of goals, the use of Gaussian mixture model Platform: |
Size: 1732608 |
Author:曾慕柳 |
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Description: 混合高斯模型是一种比高斯模型更好的背景建模方法-Gaussian mixture model is a better model than the Gaussian background modeling method Platform: |
Size: 3287040 |
Author:杨永刚 |
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Description: 混合高斯模型，用于背景建模的程序，使用时请安装OPENCV-Gaussian mixture model for background modeling procedure, the use of when you install OPENCV Platform: |
Size: 5120 |
Author:肖郎 |
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Description: 基于混合高斯模型的背景消除
利用混合高斯背景建模进行运动物体检测, 同时引入共轭先验以改进权值更新方程-Gaussian mixture model based on the background to eliminate the use of Gaussian mixture background modeling for moving object detection, while the introduction of conjugate a priori weights to improve the update equation Platform: |
Size: 94208 |
Author:Lu |
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Description: 是关于高斯混合模型的背景建模程序，是关于opencv改进的，自己编程的程序。-Gaussian mixture model on the background modeling procedure is about opencv improved, their own programming procedures. Platform: |
Size: 46181376 |
Author:ANMINGSHOU |
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Description: A common method for real-time segmentation of
moving regions in image sequences involves “background
subtraction,” or thresholding the error between
an estimate of the image without moving objects and
the current image. The numerous approaches to this
problem differ in the type of background model used
and the procedure used to update the model. This paper
discusses modeling each pixel as a mixture of Gaussians
and using an on-line approximation to update
the model. The Gaussian distributions of the adaptive
mixture model are then evaluated to determine which
are most likelyt o result from a background process.
Each pixel is classified based on whether the Gaussian
distribution which represents it most effectivelyis considered
part of the background model. Platform: |
Size: 186368 |
Author:ajinkya |
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Description: 基于混合高斯模型的背景建模方法的实现，用C++语言编写-Gaussian mixture model-based background modeling method of implementation, with C++ language Platform: |
Size: 1024 |
Author:liuli |
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Description: 利用混合高斯模型对图像序列经行背景建模，并保存。（附图片）-Using Gaussian mixture model for background modeling image sequences through the line and save. (With pictures)
Platform: |
Size: 1228800 |
Author:子西 |
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Description: 背景建模，基于改进混合高斯模型的背景建模-Background modeling, background modeling based on the improved Gaussian mixture model Platform: |
Size: 421888 |
Author:huangcolin |
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Description: 混合高斯背景建模C++源程序
在进行前景检测前，先对背景进行训练，对图像中每个背景采用一个混合高斯模型进行模拟，每个背景的混合高斯的个数可以自适应。-Before the the mixed Gaussian background the modeling C++ source. During foreground detection, background training, each background image using a Gaussian mixture model simulation, adaptive Gaussian mixture number of each background. Platform: |
Size: 7168 |
Author:sjtu-lsz |
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Description: 混合高斯模型，用于多模态场景中的背景前景检测，还特意实现了RGB前景目标的显示，用vs2010+opencv2.3.0开发-Used for background modeling, the gaussian mixture model can display the backgrounds, prospects. Can be used for multimodal, Platform: |
Size: 27008000 |
Author:chenfang |
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Description: 采用高斯混合模型用于运动背景建模，可以检测出前景-Gaussian mixture model for motion background modeling, can detect the foreground Platform: |
Size: 13082624 |
Author:曾叶 |
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Description: 提出了一种基于模型切换的背景建模方法(M SBM ).该方法以嫡图像为纽带, 实现了不同精细程度的背景模型在空间上的自适应选取和在时间上的自适应切换.对于亮度分布复杂度高的背景区域采用精细的模型以保证运动目标检测的精度,反之采用简单的模型以降低计算量
.通过模型结构自适应结合参数自适应, 很好地兼顾了检测精度和计算代价.墓于高斯混合模型和时间平均模型的双模型切换式运动目标检测算法被用于实验研究, 结果表明这种算法的检测效果和单独采用高斯混合模型的检测效果相当, 而计算速度却比后者提高很多-Proposed a model of background modeling method switching (M SBM) Based on the method of entropy image as a link, to achieve different degrees of background model in the fine spatial adaptive selection and adaptive switching in time. For high brightness distribution complex background area using sophisticated models to ensure the accuracy of the moving target detection, whereas a simple model to reduce the amount of computation
By combining adaptive parameter adaptive model structure, a good balance between detection accuracy and computational cost dual model tomb on Gaussian mixture model and the time-averaged model switched moving target detection algorithm is used for experimental research results show that the detection algorithm using Gaussian mixture model and a separate testing results have been very, and improve computing speed than many of the latter Platform: |
Size: 851968 |
Author: |
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Description: 针对子块级背景建模方法无法保证所提取前景形状的精确性及像素级背景建模方法无法有效处理非平稳场景的问题，提出了一种背景建模分层模型，首先采用文中子块级建模算法得到较为粗糙的背景区域和前景区域，然后利用混合高斯模型对特定图像区域执行像素级的前景提纯或背景模型更新操作，2 种不同层次的算法通过非
对称前向反馈机制进行级联。实验结果表明，所提分层模型在能够有效处理非平稳场景的同时保证了所提取前景
形状的精确性，且对光照突变不敏感，建模效果优于级联算法中任一独立算法，而处理时间小于2 种独立算法处理时间之和，满足了实时处理要求-Block-based background modeling couldn’t obtain the exact shape of foreground, while pixel-based approaches
couldn’t handle non-stationary backgrounds effectively. To solve the problem, a hierarchical scheme for background
modeling was presented. The hierarchical model used block-based method proposed to obtain coarse background and foreground
regions firstly, and then the operations of pixel-level foreground refining and model updating based on Gaussian
mixture model were performed on special regions of the input image. These two algorithms in different levels were combined
by adopting an asymmetric feed-forward strategy. Experimental results show that the hierarchical method proposed
can obtain the exact shape of foreground and process non-stationary scenes well, in addition, it is insensitive to illumination
change and can provide better results than any single approach in it, meanwhile, the integrated computation time is
shorter than the sum of those of running the block an Platform: |
Size: 463872 |
Author: |
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Search - Gaussian Mixture Model background modeling