搜索资源列表
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Used for OpenCV gaussian background foreground segmentation-Used for OpenCV gaussian background foreground segmentation
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淘特站内搜索引擎是由淘特JSP搜索引擎发展而来，系统基于Lucene.Net核心，通过高效的中文分词算法将数据库中内容进行分析、索引并保存至硬盘中。前台搜索时，通过读取索引文件查询，避免了传统数据库查询在高并发及海量数据下的性能问题。因前台搜索不在连接数据库，为不希望数据库放到前台的特殊用户群体提供了数据快速查询解决方案。
-Amoy Special Site search engine from the Amoy special JSP search engine developed fr
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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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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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最经典之做，保证别人没有上传过实现文章“GrabCut" Interactive Foreground Exttraction using Iterated Graph Cuts用graphcut实现图图像分割，效果非常好
-The most classic to do, to ensure that others have not uploaded the article " GrabCut" Interactive Foreground Exttraction usin
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淘特站内搜索引擎(C#版)基于Lucene.Net核心，通过高效的中文分词算法将数据库中内容进行分析、索引并保存至硬盘中。前台搜索时，通过读取索引文件查询，避免了传统数据库查询在高并发及海量数据下的性能问题。因前台搜索不在连接数据库，为不希望数据库放到前台的特殊用户群体提供了数据快速查询解决方案。
-Amoy special stations within the search engine (C# version) is based on Lucene.Net core through e
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自己写的分块分割算法，适合于场景比较复杂的物体前景背景分割。-Write their own block segmentation algorithm, suitable for more complex scene foreground and background of the object segmentation.
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a novel algorithm for fast tracking of generic objects in videos. The algorithm uses two components: a detector that makes use of the generalised Hough transform with pixel-based descr iptors, and a probabilistic segmentation method based on global m
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利用基于直方图的自适应阈值方法实现分割前景与背景-The use of adaptive threshold method of histogram based segmentation of foreground and background
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根据概率密度分布，分割前景与背景，附有实验图片-According to a probability density distribution, segmentation foreground and background, experiment with picture
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首先基于高斯模型进行目标分割，接着将分割出的前景信息作为跟踪目标，实现前景目标的实时跟踪。-Firstly, the target segmentation is performed based on the Gaussian model, and then the foreground information is used as the tracking target to realize the real-time tracking of the foreground target.
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OTSU算法也称最大类间差法，有时也称之为大津算法，被认为是图像分割中阈值选取的最佳算法，计算简单，不受图像亮度和对比度的影响，因此在数字图像处理上得到了广泛的应用。它是按图像的灰度特性,将图像分成背景和前景两部分.(Difference method OTSU algorithm called maximum class, sometimes called the Otsu algorithm, is considered to be the best algorithm, threshold
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