搜索资源列表
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A better version of guassian mixture model for background subtraction and foreground detection, using matlab and c language to implement it.
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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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This paper proposes a novel document image
binarization approach based on stroke neighborhood
enhancement. First, foreground pixels are initially
labeled. Then, the strokes are enhanced based on their
neighborhood information which include gr
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自动前背景分割，基于超像素、形状和外观前验概率及图切割-A novel foreground/background segmentation
algorithm that attempts to segment the interesting
objects from the rest of the image.The model includes a geometric prior and an appearance
prior, whose parameters are lear
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复杂背景下的前景检测，这篇文章被引用的比较多，值得学习-foreground detection from video in complex background
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背景图片与前景图的相结合，使其不突兀。需要与实际相结合来实践。-Background image and foreground figure combined, so that it does not look. Need to practice with the actual combination.
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基于高斯的前景检测，用于从背景中将前景物体分离出来。-Based on Gaussian prospects detection, for foreground objects from the background will be separated.
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一个鲁棒 matting 的程序，可生成trimap，可手动画出前景，背景，trimap，提取图像-A robust matting program can generate trimap, you can manually draw the foreground, background, trimap, extract images
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背景差分法，视频程序，分离出了前景和背景-Background difference method, video program, separating the foreground and background
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针对子块级背景建模方法无法保证所提取前景形状的精确性及像素级背景建模方法无法有效处理非平稳场景的问题，提出了一种背景建模分层模型，首先采用文中子块级建模算法得到较为粗糙的背景区域和前景区域，然后利用混合高斯模型对特定图像区域执行像素级的前景提纯或背景模型更新操作，2 种不同层次的算法通过非
对称前向反馈机制进行级联。实验结果表明，所提分层模型在能够有效处理非平稳场景的同时保证了所提取前景
形状的精确性，且对光照突变不敏感，建模效果优于级联算法中任一独立算法，而处理时间小于2 种独立算法处
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初始化 统计背景模型，用背景差法提取前景图像，并使得背景不断刷新-First initialized, statistical background model, background difference to extract foreground and background model constantly refreshed
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基于meanshift/camshift的视频运动目标跟踪实现，通过鼠标手动选择跟踪目标。基于HSV空间模型，可手动调节H S V的阈值，显示前景、背景、反响投影图。开发工具是VS2008、OPENCV.-Based meanshift/camshift video moving target tracking achieved manually using the mouse to select the target track. HSV space model, you can manual
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高斯处理视频并跟踪运动做前景背景分割-Gauss processing video and tracking the movement to do the foreground background segmentation
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平均背景法是一种学习背景场景和分割前景目标的简单方法。这种方法只能用于背景场景中不包含运动部分。而且，这种方法还要求光线保持不变，比如室内静止场景。-Average background method is a simple way to split the background and foreground objects scene study. This method can only be used for background scene does not contain moving
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前景检测程序，MATLAB实现，有背景差分，帧差法，混合高斯模型，光流法。-Foreground detection procedures, MATLAB, background difference, frame difference method, the gaussian mixture model and optical flow method.
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bgslibrary是一个开源前景背景分割库，包含了一些最新前背景分割算法。(Bgslibrary is an open source Foreground Background Segmentation library, which contains some latest background segmentation algorithms.)
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21.【高斯处理视频并跟踪运动做前景背景分割】bgfg2(21. [Gauss processing video and tracking movement, foreground background segmentation] bgfg2)
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动态目标跟踪，静态背景，前景背景动态目标提取(Dynamic object tracking, static background, foreground background, dynamic object extraction)
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动态目标追踪和前景背景提取，使用Python和opencv编程(Dynamic object tracking and foreground background extraction, using Python and opencv programming)
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