搜索资源列表
GaussBackground
- 对图像序列进行高斯背景分析，去除背景和噪声，参见文章“Automatic Temporal Segmentation for Content-Based Video Coding”。-right image sequences Gaussian background analysis, and remove background noise, see the article "Automatic Segmentation for Temporal Con tent-Based Vide
MultiGaussian
- 视频监控，图像序列运动目标识别。基于多高斯背景模型，可实时实现运动目标的自动检测。-video surveillance, image sequence moving target identification. For more background Gaussian model, the immediate goal of the campaign to achieve automatic detection.
motion-detection-techniques
- 研究了基于混合高斯模型的运动目标检测技术,在分析了混合高斯模型的基本原理的基础上,使用了一种改进的混合高斯模型更新算法.在Visual C++6.0中利用OpenCV完成了相关算法,成功地提取出了运动目标和实验场景的背景,验证了该改进的混合高斯模型更新算法的可行性-OpenCV-based motion detection techniques I have read some articles, I feel you can, share
背景建模法
- 介绍当前几种比较常见的背景建模方法，例如高斯，码本，均值等
demo
- 利用训练集训练一个高斯模型，进行运动目标的提取（文件中包含数据集）(Use the training set to train a Gaussian model to extract the moving object (the file contains the data set))
mixture_of_gaussian
- 利用混合高斯模型对一个图像序列或视频进行背景的去除，检测运动目标(Using the mixed Gaussian model to remove an image sequence or video background, or detect the moving target.)
混合高斯matlab程序
- 基于混合高斯的matlab仿真程序，用于背景提取和运动目标检测！！
21
- 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)
一问 + 二问 VIBE_Code
- 用混合高斯模型进行背景处理，并能过滤微小的扰动，适用于动态背景(Use the mixed Gaussian model for background processing and to filter tiny perturbations for dynamic background)
code
- 初步尝试使用单高斯模型进行背景建模与跟踪提取，采用形态学方法，对于背景单一的场景，提取效果还可以。(Preliminary attempts are made to use single Gauss model for background modeling and tracking extraction. Morphological method is used to extract the effect from a single scene.)
GMMmatlab程序
- 混合高斯模型，用于背景变化无抖动的目标的前景提取(The hybrid Gauss model is used for foreground extraction of background invariant targets without jitter)
单高斯程序
- 单高斯算法用于静态背景下显著目标的拾取该方法较为简单，也能应对静态背景下的目标拾取。(Used for picking up salient objects in static background)
BackGround-Fore-Detect
- 包含一些常见的运动目标检测算法，有背景模型算法，混合高斯模型算法，帧差法，经典的CB法，所有源码皆可运行。(This package include some common Moving Object Detection algorithm.Such as the BgModel,CodeBook and Gaussian-mixture-model.)
BeiJingFenLi2
- 混合高斯背景建模进行背景分离，在实行膨胀腐蚀操作提取运动目标特征(Mixed Gaussian Background Modeling for Background Segmentation, Extraction of Moving Target Features During Erosion Operation)
Signal detection and estimation codes
- P1:DC电平估计，在高斯白噪声背景下对一电平为1的直流信号进行测量。 P2:ROC曲线绘制 与实际仿真。(The frequency measurement system under Gauss's white noise)
gaussianBkModelTest
- 采用混合高斯模型，实现对监视背景的建模，有利于下一步运动目标的检测(The mixed Gauss model, modeling of monitoring background, is conducive to the detection of moving target next)
gaosibeijing2
- 高斯背景建模，用于背景搭建，背景更新速度更为快速(Gauss background modeling is used for setting up background, and the speed of background updating is faster.)
高斯处理视频并跟踪运动做前景背景分割
- 采用opencv 高斯处理视频并跟踪运动做前景背景分割(Gauss processes video and tracks motion to do foreground and background segmentation.)
Experient4
- 利用opencv高斯混合背景建模，并进行开闭运算滤波， 提取视频监控中的车辆(Using opencv Gaussian mixture background modeling and opening and closing operation filtering to extract vehicles in video surveillance)
背景差分法
- 基于阈值的高斯混合模型的背景差分法，适合初学者(Background difference method based on threshold-based Gaussian mixture model, suitable for beginners)