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本代码是Foreground-Background Segmentation of Video Sequences的配套程序，利用KDE算法对avi进行处理，从而提取前景和背景，在windows, Visual C++下测试成功
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This algorithm is presented as an alternative to graph-cuts. The operation is very simple, and can be thought of with a biological metaphor: Imagine each image pixel is a “cell” of a certain type. These cells can be foreground, background, undefined,
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混合高斯模型，建立背景模型，从而可以分离前景与背景,Gaussian mixture model, background model, which can be separated from foreground and background
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基于opencv的背景差法，实现前景和背景的分离。需要先配置好vc2008，然后编译执行。-Opencv background difference based method to achieve the separation of foreground and background. Need to configured vc2008, and then compile the implementation.
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是一个实用的抠图软件，软件很小，对图像的前景和背景分离效果很好-Matting is a practical software, software is very small, the image foreground and background separation worked well
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用Opencv实现的一个运动检测的程序。通过摄像头捕捉，把捕捉到的图像分为前景和背景，从而检测出运动图像。-Achieved with Opencv a motion detection process. Captured by the camera, the captured image are separated into foreground and background, to detect the moving image.
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介绍一种应用于视频运动检测中前景和背景建模分割的方法-proposes a novel method for detection and segmentation
of foreground objects from a video which contains
both stationary and moving background objects and undergoes
both gradual and sudden “once-off” changes.
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光流法之一：codebook BGS代码，参考论文Real-time foreground–background segmentation using codebook model （Kyungnam Kima,, Thanarat H. Chalidabhongseb, David Harwooda, Larry Davis），进行了简化。
实验效果：似乎噪声点太多了。-One of the optical flow method: the BGS codebook code, refer
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程序实现一个自适应阈值的算法，用以在不规则光照下从背景中提取出前景图像。-Procedures to achieve an adaptive threshold algorithm to extract the foreground from the background image in the irregular light.
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ExcelLibrary 是一个比较精致的 Excel 读写组件，还是由国人开发的。可以读写 xls 和 xlsx 格式的 Excel。支持简单的公式，可插入图片，对于格式的设置也不是很丰富，可设置单元格宽度，数据格式化显示。对字体，前景、背景色进行设置是它的局限性。 虽比不上 NPOI，但作为小巧的用来读写纯数据内容的 Excel 还是很高效的。-ExcelLibrary Excel is a more sophisticated reading and writing component,
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采用RGB模型进行阴影的检测与去除。能够显示前景、背景、去除阴影后的运动目标-RGB model with shadow detection and removal. To show foreground, background, after the removal of shadows moving target
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Image Segmentation (Foreground separated from Background).
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可实现与graph-cuts算法相似的图像分割效果. 他借用了生物形态学知识，将每一个像素视为一个细胞，这些细胞可能是前景，背景，或其他。这些细胞依据其灰度竞争获得生长，由此获得分割。-This algorithm is presented as an alternative to graph-cuts. The operation is very simple, and can be thought of with a biological metaphor: Imagine each ima
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通过单高斯来建立背景，然后用背景减法来提取情景，并对前景进行跟踪和计数。-We establis the background through the method of singal Gaussian,then use the background substration to get foreground,we are also successed to get the counts of cars and to track the cars.
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Real-time foreground–background segmentation
using codebook mode-Real-time foreground-background segmentation using codebook mode
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Tracking w/ blob detection, morphological operation (Togeather)
frames = {avi.cdata} uses the cdata from the video file
fg = extractForeground(frames) do foreground extraction
cmap = colormap(gray)
for i = 1:length(fg)
temp0{i} = edg
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针对智能视频监控中运动目标的检测，提出了一种基于字典学习的背景建模方法．结合时空域信息对视频中的每个位置进行字典学习来描述场景信息．利用背景频繁出现的特性，将字典中的词划分成描述背景的词和描述前景的词．用字典表达对应位置的结构，并根据字典中贡献最大词的属性对当前位置进行背景判断．根据判断的结果对字典进行实时更新．在公共的视频数据库上与传统的背景建模方法相比较，所提方法可以较好地检测出前景目标．-Intelligent video surveillance to detect moving tar
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21.【高斯处理视频并跟踪运动做前景背景分割】bgfg221.【高斯处理视频并跟踪运动做前景背景分割】bgfg2-Gauss processing video and tracking motion foreground background segmentationGauss processing video and tracking motion foreground background segmentation
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高斯处理视频并跟踪运动做前景背景分割，可用来做前背景分离，分离出运动物体，达到抠图的效果-Gauss video processing and tracking moving foreground background segmentation, can be used to do before the separation, separation of a moving object, to achieve the effect of Gauss matting video processin
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前景提取四种方法，好学易懂，适合初学者！(Foreground extraction)
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