Description: for the TI dm6446 platformBackground subtraction moduleMaintain a background model, which can distinguish background, foreground and theft/left pixelsShadow removal moduleDetect shadow regions in monochrome videosCamera shift detection and suppression moduleDetect of small camera shift, and suppress the false alarms due to themBlob extraction moduleExtract connected foreground and theft/left pixels as blobsTheft/left baggage distinguish moduleDistinguish theft blobs and left baggage blobs Platform: |
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Description: 最经典之做，保证别人没有上传过
实现文章
“GrabCut" Interactive Foreground Extraction using Iterated Graph Cuts
用graphcut实现图像分割，效果非常好-The most classic to do to ensure that other people do not realize uploaded article GrabCut Interactive Foreground Extraction using Iterated Graph Cuts with graphcut realize image segmentation, has very good results Platform: |
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Author:changfeng |
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Description: 使用opencv，将一个视频文件分割成多张图片。
特点：按帧提取，每帧保存为多张图片。
保存时，原来的格式是全彩的，同时转化并保存全彩图片对应的黑白图片和二值化图片。这三类图片分别存放在默认目录的video background foreground中。默认的视频文件名为默认目录下的ci.avi-Using opencv, a video file will be split into multiple images. Features: by frame extraction, each frame is saved as multiple pictures. Preserved when the original format is full color, at the same time transforming and save full-color picture black and white pictures and the corresponding binary image. These three types of images were stored in the default directory in the video background foreground. The default video file name is the default directory ci.avi Platform: |
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Author:kingbirdji |
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Description: 1.GeometricContext文件是完成图片中几何方向目标分类。
参考文献《Automatic Photo Pop-up》Hoiem 2005
2 GrabCut文件是完成图像中目标交互式分割
参考文献《“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts》
C. Rother 2004
3 HOG文件是自己编写的根据HOG特征检测行人的matlab代码
4 虹膜识别程序是下载的一个通用的虹膜识别程序，可以运行
5 GML_AdaBoost_Matlab_Toolbox是一个很好用的adaboost matlab工具箱
6 libsvm-mat-2.91-1 是用C编写的改进的SVM程序，代码质量很高，提供了matlab接口
7 SIFT_Matlab 是编写的利用sift特征进行的宽基线匹配，代码质量高
8 FLDfisher 是利用fisher 线性降维方法进行人脸识别-1.GeometricContext file is complete the picture in the geometric direction of target classification. References " Automatic Photo Pop-up" Hoiem 2005 2 GrabCut the target file is an interactive segmentation of image reference " " GrabCut " - Interactive Foreground Extraction using Iterated Graph Cuts" C. Rother 2004 3 HOG documents prepared under their own HOG Characteristics of pedestrian detection matlab code 4 iris recognition process is to download a general iris recognition program, you can run 5 GML_AdaBoost_Matlab_Toolbox is a good use of adaboost matlab toolbox 6 libsvm-mat-2.91-1 is written in C to improve the SVM procedures, code of high quality, provides a matlab interface to 7 SIFT_Matlab is prepared for the use of sift features a wide baseline matching, the code is the use of high quality 8 FLDfisher fisher linear dimension reduction method for face recognition Platform: |
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Author:张数 |
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Description: matlab中前景提取中用ostu法实现自动阈值的提取。-matlab in the foreground extraction using ostu method for automatic extraction of the threshold. Platform: |
Size: 1024 |
Author:苏柏良 |
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Description: 一个自己写的前景提取程序，采用背景减除法得到运动前景，背景通过统计平均得到。-a matlab code for foreground Extraction , using background subtraction method to get moving foreground ,and we get the background by statistical averaging. Platform: |
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Author:pengpeng |
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Description: 混合高斯背景建模用于检出背景，并提取前景，在OPENCV环境下操作进行的。是数字图像处理领域不可缺少的一种处理方式。OPENCV库里含有的函数在数字图像中的作用都是不可获取的，用起来简单又便捷，建议OPENCV从头认真学起-Gaussian mixture background modeling for the detection of background and foreground extraction, OPENCV environment in the operation. The field of digital image processing an indispensable approach. OPENCV library containing the function s role in the digital images are not obtained, it is simple and easy to use, it is recommended to learn the OPENCV seriously from the beginning. Platform: |
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Author:yuanyuan |
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Description: 利用高斯混合模型实现对图像前景的提取，效果很好-Using the Gauss mixture model for image foreground extraction, the effect is very good。 Platform: |
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Author:程栗 |
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Description: 利用平均背景去除法在食品中进行前景的提取，然后用蓝色标记前景-Using the average background removal in food foreground extraction and then the blue marker prospects Platform: |
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Author:cui |
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Description: 视频捕捉的对象中，背景通常保持不变。一般分析中关注移动的前景物体，威力提取出前景物体，需要建立背景的模型，将模型和当前帧进行比对检测前景物体。前景提取应用非常广泛，特别是在智能监控领域中。
如果有不含前景物体的背景图片，提取前景的工作相对容易，只需要比对当前帧和背景图片的不同，调用函数absdiff实现。但是大多数情况，获得背景图片是不可能的，比如在复杂的场景下，或者有光线条件的变化。因此，就需要动态的变换背景。一种简单的办法是对所观察到的图片取平均，但这样做也有很多弊端，首先，这种办法在计算背景图片的前需要输入大量的图片，其次我们进行取平均的过程中不能有前景物体进入。所以一种相对好的办法是动态建立背景图片并实时更新。-Video capture of the object and the background usually remain unchanged. General analysis focus on the prospect of moving objects, power extract prospect object, it is necessary to set up the background model, the model and comparing the current frame detection prospect object. Foreground extraction are widely used, especially in the field of intelligent monitoring.
If there is no prospect of object containing the background picture, extraction prospect work relatively easy, only need than current frame and background picture is different, absdiff called function realization. But in most cases, it is impossible for the background picture, such as in a complex scene, or a light conditions change. Therefore, it needs to the dynamic transformation background. A simple solution is to take pictures of the observed average, but this also has a lot of disadvantages, first of all, this kind of method in the calculation of the background picture first need to enter a lot of pictures, secondl Platform: |
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Author:dsfewf |
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Description: 本代码演示了固定相机在光照剧烈变化的情况下对背景和前景提取的算法改进，能够实现抗光照和噪声的有效背景建模和前景提取-This code demonstrates the dramatic changes in the light fixed camera case for background and foreground extraction algorithm improvements, to achieve an effective resistance to illumination and noise background modeling and foreground extraction Platform: |
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Author:Evan |
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Description: GRABCUTOpenCV中的GrabCut算法是依据《"GrabCut" - Interactive Foreground Extraction using Iterated Graph Cuts》这篇文章来实现的。该算法利用了图像中的纹理（颜色）信息和边界（反差）信息，只要少量的用户交互操作即可得到比较好的分割结果。如果前景和背景之间的颜色反差不大，分割的效果不好；不过，这种情况下允许手工标记一些前景或背景区域，这样能得到较好的结果。-GRABCUTOpenCV in GrabCut algorithm is based on the " " GrabCut " - Interactive Foreground Extraction using Iterated Graph Cuts" in this article to achieve. The algorithm uses the image texture (color) and the boundary information (contrast) information, as long as the amount of user interaction to obtain a better segmentation results. If the color contrast between foreground and background is not, split ineffective however, allow manual marking some of the foreground or background areas, this can get better results in this case. Platform: |
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Author:yangpeide |
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