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a background subtraction algorthim article.-a background subtraction algorthim Artic le.
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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 ,
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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
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Matlab program used for background substraction of an video sequence
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background subtraction
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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 pape
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背景差分方法实现规定路面的车流量统计。-Background subtraction method, the provisions of road traffic statistics.
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背景差法OpenCV实现程序代码,使用OPENCV实现，编译可通过。-The background difference method OpenCV program code
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Background subtraction method in opencv c-Background subtraction method in opencv cpp
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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
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基于背景差分的视频目标检测，matlab代码，-Video object detection based on background subtraction, matlab code
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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
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在VC6.0下实现静态背景下的运动目标检测，背景差分法的实现-Under the VC6.0 static background moving target detection, background subtraction method to achieve
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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 liab
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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 no
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背景差分法是采用图像序列中的当前帧和背景参考模型比较来检测运动物体的一种方法,其性能依赖于所使用的背景建模技术。背景差分法检测运动目标速度快，检测准确，易于实现，其关键是背景图像的获取。在实际应用中，静止背景是不易直接获得的，同时，由于背景图像的动态变化，需要通过视频序列的帧间信息来估计和恢复背景，即背景重建，所以要选择性的更新背景。-Background difference method is the use of images in the sequence of the current
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基于matlab，利用背景减除法实现运动目标的跟踪。本代码所用的函数均适用于新版本的matlab，不需要额外修改。在MATLAB2014a编译通过。-Based on matlab, for tracking moving objects using background subtraction method. The code used functions are applied to the new version of matlab, no additional modifications
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background subtraction for shadow detection and removal.
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根据代码路径，识别AVI格式视频前景，减除背景(Identify video foreground and background subtraction)
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In this paper, the Detection of the Moving Object is done based on Background Subtraction & Frame Differencing techniques. A moving object can be detected by employing various methods such as, by taking the difference between two Images.
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