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基于改进背景差的运动目标检测
- 改进的背景差方法
detection
- OPENCV写的运动目标识别与跟踪程序，很不错哦 -OPENCV writing campaign to target identification and tracking procedures, very good, oh
w4-moving-object-detection
- 此程序是针对视频中的运动目标的检测，程序中包括了背景建模、背景差法等功能的w4背景建模算法。-This procedure is for the video of the moving target detection, process modeling, including the background, the background difference method and other functions of the background modeling algorithm w4.
singleGaussianmodel
- 本码源是针对于单高斯模型算法做的运动目标检测，其中实现了背景建模、背景更新和目标检测的步骤实现。-The source code is in the single-Gaussian model for the algorithm to do the moving target detection, in which the realization of the background modeling, background to update and steps to achieve targe
SVD
- 线性方程的解法,实现对运动目标的检测,针对可见光图像弱小目标检测中的背景抑制和去噪问题,提出了奇异值分解(Singular Value Decomposition,SVD)-Linear equations, to achieve the detection of moving targets, in view of the weak target detection in visible light images in the background suppression and de-noi
BlockMotionestimation
- 本代码计算帧间光流场，通过阈值分割获得运动矢量，对当前帧进行补偿，配置差分后实现运动目标分割，解决复杂背景下运动目标的检测问题。-This code interframe optical flow field calculated by threshold segmentation to obtain motion vectors, to compensate for the current frame, after the implementation differential configu
RunningAvg-without-seletivity
- 此程序的功能是针对图像中的运动目标的检测，程序依照输入视频、建立背景模型、灰度化、两帧相减、检测结果的流程来书写程序。-The function of this procedure is the image of moving target detection, the procedure in accordance with the input video, the establishment of the background model, gray, and two-phase reduc
mixture_of_gaussians
- 基于混合高斯背景建模的理论思想，实现运动目标检测，检测效果理想-Gaussian Mixture Background Modeling Based on the theory of ideology, to achieve moving target detection, test results are satisfactory
blobtrack
- 针对在复杂背景中检测出多批特定运动目标并实施分配批号实行标记跟踪，本文利用OpenCV的运动物体跟踪的数据结构、函数以及基本框架，建立了一个由人机交互界面模块；运动物体的前景检测模块；运动物体的团块特征检测模块；运动物体的团块跟踪模块轨迹生成模块；轨迹后处理模块组成的视频图像运动目标分析系统。-Aim at detecting，tracking and marking multipule specific targets in complex background．We use the ba
KDE_subtraction
- 采用非参数背景建模，MFC，对运动目标进行检测，有很高的参考价值-Using non-parametric background modeling, MFC, the moving target detection, a high reference value
MovingDetect
- matlab的运动目标分割 车辆检测 平均建模背景差分-Moving object segmentation matlab Vehicle Detection average difference modeling background
Background_modeling_of_dynamic_scenes_based_on_tar
- 基于背景建模的动态场景目标检测,介绍了背景建模的步骤和重要的方法，然后介绍了根据背景差分法，来提取运动目标，从而进行跟踪-Background modeling of dynamic scenes based on target detection, background modeling described the steps and important way, then introduced under the background difference method to extract
background-difference-method
- 利用OpenCV中背景差分的函数，进行背景差分法构建，可以很好的进行运动目标检测-Background difference method based on OpenCV
RGBbackgroundSubtraction
- 运动目标检测 背景减除 摄像头捕获视频 -Motion object detection background subtraction
CvPixelBackgroundGMM
- 一种基于混合高斯背景建模算法的运动目标检测背景背景差分源程序-code of mixture Gussian Backgrand Modeling
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)
video
- 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法(1. Background prediction method background detection in static background 2. Inter-frame difference method target detection in static background 3. Mean Shift The target track
ViBe_C++背景建模算法
- 基于背景建模的运动目标检测程序，所用算法为VIBE算法(Moving object detection program based on background modeling)
背景差分
- 通过背景差分法获取运动目标检测，提取前景目标，转化成二值图(The moving target detection is obtained by the background difference method, and the foreground object is extracted and transformed into a two value graph.)
基于码书的运动目标检测方法
- 本方法提出一种基于码书的背景构造方法。首先对历史图像序列进行量化.由此每一像索点得到一本码书,其次根椐前景点和背景点在图像序列中的分布特性选择合适的码字构造背景，该方法能在有限的储存空间下表示长时间的图像序列，从而有效实现对扰动的背景物体地融合，同时克服运动缓慢 的目标融入背景，并能适应缓慢的光照变化。