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: |
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Author:曾慕柳 |
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Description: 本文通过融合图像的颜色和梯度特征 ,实现了一种实时背景减除方法。首先融合颜色和梯度特征建立新的能量函数 然后基于图切割算法最小化能量函数 ,并对前景P 背景进行分割 最后使用光流验证前景区域的真实性 ,并更新背景模型。- Based on the fusion of color and gradient features , this paper implement s a novel approach to real-time background subtraction.Firstly , an energy function is defined based on the fusion of color and gradient features. Secondly , the graph cut s based algorithm is employed to minimize energy function and segment the foreground. Finally , average optical flow is used to make inference about the validity of foreground regions , background models are then updated.
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Size: 787456 |
Author:巡洋舰 |
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Description: Example OpenCv
// Background average sample code done with averages and done with codebooks
// (adapted from the OpenCV book sample)
//
// NOTE: To get the keyboard to work, you *have* to have one of the video windows be active
// and NOT the consule window.
//
// Gary Bradski Oct 3, 2008.
//
/* *************** License:**************************
Oct. 3, 2008
Right to use this code in any way you want without warrenty, support or any guarentee of it working.
BOOK: It would be nice if you cited it:
Learning OpenCV: Computer Vision with the OpenCV Library
by Gary Bradski and Adrian Kaehler
Published by O Reilly Media, October 3, 2008
AVAILABLE AT:
http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134
Or: http://oreilly.com/catalog/9780596516130/
ISBN-10: 0596516134 or: ISBN-13: 978-0596516130
************************************************** */-Example OpenCv
// Background average sample code done with averages and done with codebooks
// (adapted from the OpenCV book sample)
//
// NOTE: To get the keyboard to work, you*have* to have one of the video windows be active
// and NOT the consule window.
//
// Gary Bradski Oct 3, 2008.
//
/**************** License:**************************
Oct. 3, 2008
Right to use this code in any way you want without warrenty, support or any guarentee of it working.
BOOK: It would be nice if you cited it:
Learning OpenCV: Computer Vision with the OpenCV Library
by Gary Bradski and Adrian Kaehler
Published by O Reilly Media, October 3, 2008
AVAILABLE AT:
http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134
Or: http://oreilly.com/catalog/9780596516130/
ISBN-10: 0596516134 or: ISBN-13: 978-0596516130
***************************************************/
Platform: |
Size: 3072 |
Author:Jason |
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Description: 学习并找到降噪方法,对语音信号背景噪声做处理,使得声音更清晰。-The background noise is the most common factor degrading the quality and intelligibility of speech in recordings. Spectral subtraction can lower the noise level without affecting the speech signal quality. In this paper, we have studied and implemented to reduce the background noise of the voice signal, and to make improvements to reduce the background noise of the experiment. Not only with the spectral subtraction of the noisy signal of the transformation, we improve the traditional spectral subtraction based on the introduction of the parameters, by adjusting the parameters(α、β、γ) to achieve better enhancement. Platform: |
Size: 398336 |
Author:zhangqing |
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Description: Background subtraction is used to extract moving objects in video frames.This algorithm is applicable for real time application.-Background subtraction is used to extract moving objects in video frames.This algorithm is applicable for real time application. Platform: |
Size: 1012736 |
Author:Rohan |
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Description: 帧间差分法从多帧连续图像提取背景 另一个是通过背景提取运动物体-Interframe difference from the background of continuous multi-frame image extraction, the other is to extract moving objects by background Platform: |
Size: 2048 |
Author:师洪德 |
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Description: 基于opencv和VC++的目标识别代码,帧差法和背景差法同时运用-While the use of target identification code based on opencv and VC++ of the frame difference method and background subtraction Platform: |
Size: 9380864 |
Author:罗俊 |
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Description: 针对背景差法易受外界环境因素影响的缺点, 提出了一种基于改进K-均值聚类的背景建模方法。通过比较任意样本与该像素位置处的子类中心之间的距离, 对各个像素的观察值进行聚类, 并在聚类过程中逐步确定其类别数。一段时间的学习之后, 样本数最多的子类就构成了背景模型。仿真结果表明, 该算法即使在运动目标存在的情况下也能准确的提取出实际的
背景, 而且显著地降低了系统的存储量。-Aimed at the disadvantage that background subtraction was liable to be affected by outside environment,
a background modeling method based on the improved K-mean clustering was provided. By comparing the distances
between certain sample and sub-class center of the pixel, observation values of the pixels were clustered and the
number of the clusters was determined during the clustering process.. After learning for a period, background model
was built by sub-class with the maximum samples. Simulations show that actual background can be extracted accurately
by the algorithm even when moving targets are existent and the memory cost of the system is reduced dramatically Platform: |
Size: 1495040 |
Author: |
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Description: 将背景减法中应用的基于像素的背景建模方法分为递归和非递归两类,分别对它们的算法进行综述,总结它们适用的场合和更新状况 并对各种算法性能从精确度、时、空复杂度3 个方面进行比较 最后对背景建模方法的发展和应用方向作总
结和展望。-Pixel-based background modeling methods which generaly used in the background subtraction are divided into two types: recursive and nonrecursive.
Firstly,the background modeling mothods are reviewed,and their possible applications and update status are summarized. Secondly,the performance of methods are compared arrording to their accuracy,time complexity and space complexity. Finally,the development and application of background modeling method are summaried and outlooked. Platform: |
Size: 176128 |
Author: |
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Description: * Please note that this not an implementation of the complete system
* given in the above papers. It simply implements the temporal media background
* subtraction algorithm.-* Please note that this is not an implementation of the complete system
* given in the above papers. It simply implements the temporal media background
* subtraction algorithm. Platform: |
Size: 11264 |
Author:cuongeuro |
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