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搜索资源 - Foreground Segmentation
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自己用opencv写的手势识别的软件。界面简单点,用动态前景分割肤色模型和直方图反演分割手部区域,然后用模式识别方法搞定识别问题。绝对原创,以后可能再也不搞这方面了,传上来跟大家分享-Own use opencv gesture recognition software to write. Interface simply, skin color model with dynamic foreground segmentation and histogram segmentation of ha
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图像前景分割 运用了新的算法和投票机制 该算法目前是最好的-Image foreground segmentation and the use of the new algorithm and the voting mechanism of the algorithm is best
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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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Image Segmentation (Foreground separated from Background).
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This package contains m-files for the segmentation of a moving foreground from video with a static background
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Adaptive foreground and shadow segmentation using hidden conditional random fields.rar-Adaptive foreground and shadow segmentation using hidden conditional random fields.rar
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两次利用大津法对图像进行分割,将前景与背景,白色区与背景分割开,并二值化。-Otsu method twice using image segmentation, the foreground and background, white background area and separate, and binary.
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Used for OpenCV gaussian background foreground segmentation-Used for OpenCV gaussian background foreground segmentation
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基于区域融合的半监督的图像分割算法。首先在背景和前景手动设置初始分割标记,在迭代过程中不断通过区域融合操作获得最大相似度的区域,从而实现目标分割。-Regional integration based on semi-supervised image segmentation. First of all, in the background and foreground segmentation manually set the initial marking, in the iteration
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原始snake matlab 源碼,簡單版- seg = localized_seg(I,init_mask,max_its,rad,alpha,method)
Inputs: I 2D image
init_mask Initialization (1 = foreground, 0 = bg)
max_its Number of iterations to run segmentation for
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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 people in a dense crowd is a challenging problem
for a single camera tracker due to occlusions and extensive
motion that make human segmentation difficult. In this
paper we suggest a method for simultaneously tracking all
people in a
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从静止的视频背景中,分割出前景目标的程序-Uses graph cuts to segment foreground objects from a static background in video. Morphology and Segmentation. foreground segmentation,
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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
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迭代法是基于逼近的思想,逼近的目标是使得:前景和背景的平均灰度值的平均值即为阈值。该方法的原理是:如果用某一阈值分割出的图像,其两部分平均值的中值,正好等于该阈值,那么这个阈值就是所求的阈值。-Iterative method is based on the approximation of the idea of approaching the goal is to make: the foreground and background is the average
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Real-time foreground–background segmentation using codebook model
了解码书进行图像处理(背景与前景)的原理,可以从该文章中获得有益的参考价值-Real-time foreground–background segmentation using codebook model
A practical paper for knowing of image processing theory(about foregro
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使用背景建模法和时间差分法的前景分割,使用找轮廓的方式显示移动物体的位置-Background modeling using time-difference method and the prospect of partition, use the display profile to find the position of moving objects
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分五个部分讲解:1.计算分割函数。图像中较暗的区域是要分割的对象。
2.计算前景标志。这些是每个对象内部连接的斑点像素。
3.计算背景标志。这些是不属于任何对象的像素。
4.修改分割函数,使其仅在前景和后景标记位置有极小值。
5.对修改后的分割函数做分水岭变换计算。-Divided into five sections explain: (1) Calculate the partition function. The dark areas in the image is the
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这是一份我自己收集的近期(2010-2012)关于前景分割方面的文章,里面有关于前景分割新的思想-This is a copy of my own collection of recent (2010-2012) article on the foreground segmentation, there are new ideas about the prospect of partition
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背景建模和前景分割的方式把运动车辆提取出来。并进行最近临关联,输出目标轨迹。
MeanShift运动目标跟踪 matlab程序
1.截取跟踪目标矩阵rect
2.求取跟踪目标的加权直方图hist1
3.读取视频序列中的一帧, 先随机取一块与rect等大的矩形,计算加权直方图hist2。
4.计算两者比重函数,如果后者差距过大, 更新新的矩阵中心Y,进行迭代(MeanShift是一种变步长可以迅速接近概率密度峰值的方法),直至一定条件后停止。
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