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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
CarCount
- 该代码实现车辆的检测，采用了训练的方式，从视频中提取背景，然后做差分，连通域提取等步骤得道前景。该代码采用OPENCV实现。-The code to achieve vehicle detection, using training methods to extract from the video background, and then do differential, connected components extraction and other steps to attain the
BeiJingJianMo
- 基于C#的视频前景检测与背景建模，包括实现代码和论文解释。-C#-based video background modeling and foreground detection, including the implementation code and the paper explains.
12752432detect_motion
- 智能视频监控运动目标检测,检测目标运动，前景和背景区分-Moving object detection, intelligent video surveillance, detection of target motion, foreground and background distinguish
m
- 智能视频监控运动目标检测,检测目标运动，前景和背景区分-Moving object detection, intelligent video surveillance, detection of target motion, foreground and background distinguish
beijingfa
- 在vc++6.0下，利用opencv函数库，使用背景差分法检测车辆，并显示背景帧，和前景帧-Use opencv library in vc++6.0, using the background subtraction method detects the vehicle, and the background frame, frame and prospects
jj
- 三帧差法的实现，用于动态目标检测，分出背景和前景-Three implementation of frame differential method for dynamic target detection, the background and foreground
hsv_ViBe
- ViBe是一种像素级视频背景建模或前景检测的算法，效果优于所熟知的几种算法，对硬件内存占用也少，图像特征提取，(ViBe is a pixel level video background modeling or foreground detection algorithm is better than several well-known algorithms, hardware memory footprint, image feature extraction)
背景差分法检测运动目标
- 背景差分法检测目标，用于背景为静态的，检测目标，背景图像与前景图像相分离(Background subtraction is used to detect targets for static background)
webcode_static background
- 根据代码路径，识别AVI格式视频前景，减除背景(Identify video foreground and background subtraction)
trackingMethodsOnCar
- 目标检测，对包含动态背景信息的监控视频，设计有效的前景目标提取方案。(Target detection, an efficient foreground object extraction scheme is designed for surveillance video with dynamic background information.)
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.)
caffeine
- 现有的显着性检测方法使用图像作为输入，并且对前景/背景相似性，复杂背景纹理和遮挡敏感。我们探讨了使用光场作为显着性检测的输入的问题。(Existing saliency detection approaches use images as in-puts and are sensitive to foreground/background similari-ties, complex background textures, and occlusions. We ex-plore the pro
multiObjectTracking
- 该程序是用混合高斯建模+卡尔曼滤波实现，结果依赖于前景检测效果，结果效果较好，但背景干扰较多。(The program is to use mixed gaussian modeling + kalman filter implementation, the result depends on the foreground detection results, the effect is better, but more background interference.)