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backmode824
- 这个是应用混合高斯的背景建模的方法进行的目标检测的程序,需要应用opencv.供大家交流交流-this is the application of Gaussian mixture of the background modeling method for the detection procedures, opencv needed. for the exchange of exchange
bkgrd
- 基于opencv开源图像库作的一个背景检测的程序，要在图像处理软件中使用的加，对算法作了改进-opencv revenue based on the images for the detection of a background procedure, in the image processing software used in Canada, the algorithm has been improved
background__modelling
- 利用高斯模型实现背景建模的程序。简单实用，自己写的，利用了opencv的处理函数，需要调节阈值-using the Gaussian model, background modeling procedures. Simple and practical, wrote, opencv use of the processing function, needs to adjust the threshold
backprojection
- 是一用opencv实现的背景减出的代码，可以参考一下-with opencv is a realization by the background of a code can reference
opencvexample
- 使用vc++和opencv编写的读取视频文件和运动检测的例子，其中包括自适应背景更新的方法。-use vc opencv prepared and read documents and video motion detection example, These include adaptive background updating methods.
ren_opencv_1
- 这是我根据\"opencv-人脸识别\"和\"背景建模，运动物体检测\"两个程序结合的,内附了我自己合成的 英文版opencv.chm的电子书，希望对大家有帮助，运行程序时请修改cvLoad函数的路径到自己的 OpenCV\\data，该程序主要是通过摄像头读取，边检测边分析人脸的功能-under "opencv-face recognition" and "background modeling, Moving Object Detection
backrecognize
- 基于opencv的背景建模，运动物体检测-opencv based on the background of modeling, detection of moving objects
Background_Extract
- 基于OpenCV开发的道路交通视频的背景提取和前景提取。可对道路的背景进行提取和实时更新，从而提取出运动的车辆。
openCV_BGExtract
- 基于openCV得高斯背景模型提取。需要openCV，内置测试视频
BackGround
- 由视频提取出背景，是动态提取背景的问题，调用了opencv中的几个函数
用光流法进行运动目标检测
- 采用光流法形式检测背景相对稳定的运动物体，编写语言为C++，所有视觉库为opencv(The optical flow method is used to detect moving objects with relatively stable background. The language is C++, and all visual libraries are OPENCV)
opncv
- 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)
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)
第一种方法的输出
- 背景减除提取前景并保存前景视频，利用的是opencv python(Background subtraction extracts foreground and saves foreground videos)
SmokeDetection
- 两种烟雾处理的方法可以有效的提取前景和背景，并且具备保存功能。相比较其他方法这两种方法是可以直接使用的没有错误。(Two kinds of smoke treatment methods can effectively extract the foreground and background, and have the preservation function. Compared with other methods, the two methods can be used directly
Edge detection
- 目标检测首先利用统计的方法得到背景模型，并实时地对背景模型进行更新以适应光线变化和场景本身的变化，用形态学方法和检测连通域面积进行后处理，消除噪声和背景扰动带来的影响，在HSV色度空间下检测阴影，得到准确的运动目标。(object detectWe use statistical methods to obtain the background model, and real-time of the background model is updated to adapt to illumina
Debug
- opencv实现视频处理运动目标检测，使用帧差法，但是易受背景噪声影响(Opencv implements video processing moving target detection, using frame difference method, but it is easily affected by background noise.)
fall
- 混合高斯背景建模与CamShift算法结合的基于openCV的视频目标跟踪(OpenCV based video target tracking combined with hybrid Gauss background modeling and CamShift algorithm)
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)
使用python调用摄像头数据实现虚拟背景
- 基于python+pytorch+opencv实现的复杂环境下的虚拟背景功能