Description: 基于混合高斯背景建模的方法用于检测场景中的运动车辆，采用Visual C++和OpenCV实现，程序有详细注释，并且附带测试视频，希望对大家有帮助。-The movement of vehicles, based on Gaussian mixture background modeling method for detecting the scene to adopt the Visual C++ and OpenCV realization, procedures detailed notes, and come with a test video, hope everyone. Platform: |
Size: 7834624 |
Author:离逝的风 |
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Description: 混合高斯背景建模，基于HSV空间的阴影去除，直接打开avi文件即可运行得到理想的结果-Gaussian mixture background modeling, shadow removal based on HSV space, directly open the avi file to run to get the desired results Platform: |
Size: 164864 |
Author:高东旭 |
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Description: 这段代码是在matlab上运行的，能实现对视频的图像处理，即高斯混合背景建模方法。-This code is run in matlab that can realize the video image processing, namely Gaussian mixture background modeling method. Platform: |
Size: 2048 |
Author:念小念52 |
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Description: vs2010工程，C++（优化了opencv的代码），通过混合高斯背景建模实现的运动物体检测，效果非常好。-vs2010 project, C++ (optimized opencv code), Gaussian mixture background modeling to achieve through the detection of moving objects, the effect is very good. Platform: |
Size: 107520 |
Author:张林 |
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Description: 混合高斯背景建模的EM估计算法，是一篇英文资料，希望对大家有帮助。-EM estimation algorithm for Gaussian mixture background modeling, is an English data, we want to help. Platform: |
Size: 93184 |
Author:lijie |
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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: |
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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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