搜索资源列表
movingtargettracking
- 视频图像背景建模与运动目标检测 采用GMM背景建模与智能更新，能够实时实现视频智能监控动目标检测，可用于视频行为识别、视频事件检测。
vb_opencamera
- VB程序，简单方法打开摄像头，可供参考，制作动目标检测-VB open your camera
TBD
- 有效的用于雷达弱目标检测的算法 规划算法进行弱目标检测的机理研究 粒子滤波红外点状动目标跟踪算法研究-An Effective Track-Before-Detect AIgorithm for Dim Target Detection
ObjectDetect
- 用matlab编写的不错的运动目标检测的源程序-Matlab prepared with a good source of moving target detection
guangliufenxi
- 光流分析程序 利用光流分析进行运动目标检测程序 -Optical flow analysis program using optical flow analysis of moving target detection procedures
Wrongsky_Moving_detect
- Wrongky方法实现运动目标检测，对微小变化不敏感-moving detect by Wrongsky method
dpca
- 基于DPCA算法的动目标检测，非常实用，希望对你有帮助-DPCA-based moving target detection algorithm is very useful and would like to help you
shadow3
- 提出了一种室内静止摄像机条件下的运动目标检测和阴影抑制方法。该方法采用一种自适应的背景估计方法来实时更新 背景,用基于概率分类法检测运动目标,并在联合HMMD色彩空间和光度特征来抑制阴影之后,用Sobel边缘检测来修正运动目 标。实验结果表明,该方法能够有效地检测运动目标和抑制阴影。 -An indoor stationary camera under the conditions of moving target detection and shadow suppression m
RADAR_simulation
- 雷达成像模拟程序，可以检测动目标并标示运动方向。运行radarSimulation.m文件。可以自由设置参数。-Simulation of radar imaging procedures, can detect the moving target and marked the direction of movement. RadarSimulation.m file to run. Are free to set the parameters.
MovingTargetDetect
- 研究生机器视觉课程的大作业 运动目标检测 -moving target detect
videotrack
- 基于VC++的的meanshift算法动目标识别程序-Based on the moving target identification procedures meanshift
direct-data-domain-method-for-ground-moving-ta
- 一种有效的直接数据域地面动目标检测方法An effective direct data domain method for ground moving target detection-An effective direct data domain method for ground moving target detection
basedonOpenCV
- 基于OPENCV的动目标检测《基于OPENCV的动目标检测 》 -the technology of catching moving target based on OpenCV
haizabo3
- 好文章，海杂波FRFT域分形特征判别及动目标检测方法-good paper for sea cultter
motiondetetor
- 动目标检测 wince下成功实现，带预览功能，十分强大-Wince under the moving target detection
test2
- 对视频序列中的运动目标进行检测与跟踪，动目标检测部分采用背景差分法，跟踪部分采用卡尔曼滤波，检测结果用红色外接矩形框表示，跟踪结果用绿色矩形框表示 2、采用平均背景法更新背景图像。(The moving target in the video sequence is detected and tracked, the moving target detection part uses the background difference method, the tracking part uses