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Description: Gaussian Kernel Density Estimation with Bounded Support
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Size: 48128 |
Author: baolij |
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Description: 自适应核密度估计运动检测方法
提出一种自适应的核密度(kernel density estimation, KDE)估计运动检测算法. 算法首先提出一种自适应前景、背景阈值的双阈值选择方法, 用于像素分类. 该方法用双阈值能克服用单阈值分类存在的不足, 阈值的选择能自适应进行, 且能适应不同的场景. 在此基础上, 本文提出了基于概率的背景更新模型, 按照像素的概率来更新背景, 并利用帧间差分背景模型和KDE分类结果, 来解决背景更新中的死锁问题, 同时检测背景的突然变化. 实验证明了所提出方法的适应性和可靠性.-Adaptive kernel density estimation method of motion detection of an adaptive kernel density (kernel density estimation, KDE) estimated motion detection algorithm. Algorithm first proposed an adaptive prospects, the background of the dual-threshold threshold selection method for pixel classification. The method used to overcome the dual-threshold single classification threshold shortcomings, the choice of threshold can be adaptive, and able to adapt to different scenes. On this basis, this paper, based on the probability of the background update model, in accordance with the probability of pixels to update the background, and take advantage of interframe differential background model and the classification results of KDE, to resolve the deadlock in the background update, while detection of abrupt changes in the background. Experiments show the proposed method of adaptability and reliability.
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Size: 1480704 |
Author: maolei |
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Description: 视频背景非参数估计论文及matlab实现.matlab代码只实现了灰度图的背景估计，论文利介绍的彩色视频处理方法可以自己看看怎么做。-Background and Foreground Modeling Using
Nonparametric Kernel Density Estimation for
Visual Surveillance
AHMED ELGAMMAL, RAMANI DURAISWAMI, MEMBER, IEEE, DAVID HARWOOD, AND
LARRY S. DAVIS, FELLOW, IEEE
Invited Paper
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Size: 258048 |
Author: flora |
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Description: kde全称是kernel density estimation.基于核函数的概率密度估计方法。是模式识别中常用的算法之一-KDE which is kernel density estimation is used to estimate probabilty function. It is mostly used in pattern recogntion
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Size: 2274304 |
Author: herman |
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Description: fast and accurate state-of-the-art bivariate kernel density estimator
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Size: 4096 |
Author: yyz |
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Description: 一种核密度估计，或者称作带宽选择的方法，可以估计二维尺度参数，至于多维以上的估计方法尚在开发，多维情况下个人经验好的方法是多次实验取较好值-kernel density estimation, bandwidth selection, two-dimensional scale parameter can be estimated ,for the multi-dimensional approaches are still under development, multi-dimensional cases, personal experience is to do the experiment many times
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Size: 623616 |
Author: 苗晨 |
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Description: Kernel Density Estimation (Set of tools for nonparametric (kernel) density estimation)
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Size: 1086464 |
Author: 陳偉 |
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Description: Bivariate Kamma Kernel Density Estimate
for large data set-optimize method
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Size: 43008 |
Author: |
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Description: Gaussian Kernel Density Estimation Demonstration
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Size: 49152 |
Author: siminov |
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Description: 以为高斯和密度估计，使用高斯核的非参数密度估计方法，对样本进行概率密度估计，程序中给出了窗宽的估算公式。-That the Gaussian and density estimation, using Gaussian kernel non-parametric density estimation method, the sample probability density estimates, the program gives the formula for bandwidth estimation.
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Size: 1024 |
Author: william |
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Description: Reliable and extremely fast kernel density estimator for one-dimensional data
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Size: 2048 |
Author: samy |
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Description: 核密度估计 R语言编写的源代码 直接下载 帮助文件-Kernel density estimation written in R source code to download the help file
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Size: 4096 |
Author: qiaojian |
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Description: estimate kernel density in matlab
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Size: 15360 |
Author: wal |
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Description: 一篇核密度估计资料，一种新的核函数选择方法-A kernel density estimate data，A new kernel selection method
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Size: 201728 |
Author: zhou |
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Description: KDE function or kernel density function for the estimation of a continuous density
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Size: 62464 |
Author: muddaththir |
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Description: 一篇引用率非常高的英文文献，基于快速高斯的KDE目标跟踪-Efficient kernel density estimation using the fast gauss transform with applications to color modeling and tracking
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Size: 100352 |
Author: 元十三限 |
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Description: 核密度估计的源码，kernel density estimation，从官方渠道获得-Source kernel density estimation, kernel density estimation
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Size: 3072 |
Author: zz |
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Description: 本程序是核密度函数的运用。对于大量的数据，而且分部成离散状态时，采用核密度分析是有效的。-This procedure is to use kernel density function. For large amounts of data into discrete segments and state, the use of nuclear density analysis is valid.
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Size: 406528 |
Author: wuhui |
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Description: Kernel density estimation
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Size: 59392 |
Author: 刘 |
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Description: 核密度估计得背景提取的改进，通过关键桢获得背景模型(Improvement of background extraction of kernel density estimate)
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Size: 2048 |
Author: sunjianfen
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