搜索资源列表
opencv
- 运用高斯混合背景法对背景建模的背景差分法运动目标检测。-Background method using Gaussian mixture background modeling background subtraction method to detect moving targets.
WHLL
- 基于背景差分的运动目标检测与跟踪程序,适合初学者练习和学习使用-Based on background subtraction moving target detection and tracking, which is suitable for beginners to practice and learn to use.
GMM
- 针对摄像机固定下的复杂背景环境,对采集到的视频图像的图像数据用混合高斯背景建模方法实现前景/背景分割,实现运动目标检测和跟踪。在进行前景检测前,先对背景进行训练,对图像中每个背景采用一个混合高斯模型进行模拟,每个背景的混合高斯的个数可以自适应。然后在测试阶段,对新来的像素进行GMM匹配,如果该像素值能够匹配其中一个高斯,则认为是背景,否则认为是前景。由于整个过程GMM模型在不断更新学习中,所以对动态背景有一定的鲁棒性。最后通过对一个有树枝摇摆的动态背景进行前景检测,取得了较好的效果。-For c
matlab_beijingchafen
- 使用MATLAB实现运动目标检测,用的是背景差分法-moving detection by matlab
VC_moving-dec
- VC编程实现运动目标检测,背景差分,亲测可用哦-VC programming to realize moving target detection
jianche
- 背景差分建模运动目标检测和跟踪,附有一个实验视频,点开就跑
opencv--jiance
- 基于visual和opencv的运动目标检测,背景差分法-Opencv based on visual and moving target detection, background subtraction
lkof
- 基于光流法的缓慢旋转背景中的运动目标检测算法-Target Detection based on optical flow
ViBe_seg
- 基于opencv2.4.5的运动目标检测,利用vibe背景建模方法-moving targets detect based on vibe
finalcode
- 基于帧差法的运动目标检测,可以实现静止背景下的运动目标检测-Based Moving Target Detection frame difference can be achieved moving target detection under static background
BJchafen
- 基于背景差分法的运动目标检测,可以有效解决帧差法的空洞、细小连接等问题-Based moving target detection background subtraction method can effectively solve the empty frame difference, the small connection problems
nonparametric-background-generation
- 背景建模-非参数背景生成,应用于运动目标检测-Background modeling- nonparametric background generation, used in moving object detection
000214
- 对运动目标检测所用背景减除法进行的检测程序,有高斯法,均值法,-Background subtraction division for the moving target detection test procedure, a gaussian method, average method,
beijingxiangjian
- 基于opencv的运动目标检测,采用了混合高斯和背景相减两种方法,带源码,希望有点用-Opencv based moving target detection, using a mixture Gaussian and background subtraction of two ways, with source code, hope Somewhat
detect
- 基于opencv的运动目标检测,运用帧间差分法对静态背景环境下的运动目标进行检测-Opencv based moving target detection, the use of inter-frame difference method for moving objects static background environment for testing
detection
- 基于opencv的运动目标检测,运用帧间差分法对静态背景环境下的运动目标进行检测-Opencv based moving target detection, the use of inter-frame difference method for moving objects static background environment for testing
asdf
- 运动目标检测是将位置发生改变的物体从背景中提取出来,它是运动目标跟踪、行为识别 和场景描述等技术的基础。运动目标检测的经典方法有光流法、帧间差分法和背景减除法。-Moving object detection is to change the position of the object extracted the background, it is a moving target tracking, behavior recognition And underlying techno
vibe
- Vibe,通用环境下运动目标检测算法,相对传统背景建模的方法,ViBe算法实时性更高,背景重建的时间短。-Vibe, motion detection algorithm under general environmental objectives, relative to traditional background modeling method, ViBe higher real-time performance, background reconstruction time is sho
mixture_of_gaussians
- 计算机视觉中最重要的研究之一就是运动目标检测,其不但在模式识别方面具有相关的研究,而且在图像理解领域也有非凡的意义。运动目标检测是通过通过图像序列帧图像来提取运动目标,通过运用相关的算法一幅图片被划分为前景点和背景点。运动目标检测算法是后续的运动目标分类、运动目标跟踪和分析提供了基础。本论文讲述了几种常用的视频运动目标检测算法,并就背景差分法进行了重点研究,通过两种方法来对比差分法的特点。其中背景差分法算法的主要流程为:视频获取、视频转化为图片序列、图片灰度化处理、去除噪声、差分图片、对图片进行
UCGECWR567
- 基于静止背景下运动目标检测中恢复背景的示例代码VC程序-Based on static background motion target detection background to recover the sample code VC program