登录
首页 » WINDOWS » 基于帧差法多目标跟踪Matlab代码

基于帧差法多目标跟踪Matlab代码

于 2017-08-31 发布 文件大小:30764KB
0 240
下载积分: 1 下载次数: 37
我要下载

代码说明：

  非常完整的帧差法多目标跟踪Matlab代码，并提供了完整的文档介绍，非常适合初学者学习。注：运行时要改一下文件路径，以及把视频文件转成图像序列输入。(Very complete frame difference method, multi-target tracking Matlab code, and provides a complete documentation, very suitable for beginners to learn. Note: at run time, you change the file path, and the video file is converted to an image sequence)

文件列表：

vlfeat-0.9.18\.gitattributes
vlfeat-0.9.18\.gitignore
vlfeat-0.9.18\apps\phow_caltech101.m
vlfeat-0.9.18\apps\recognition\encodeImage.m
vlfeat-0.9.18\apps\recognition\experiments.m
vlfeat-0.9.18\apps\recognition\extendDescriptorsWithGeometry.m
vlfeat-0.9.18\apps\recognition\getDenseSIFT.m
vlfeat-0.9.18\apps\recognition\readImage.m
vlfeat-0.9.18\apps\recognition\setupCaltech256.m
vlfeat-0.9.18\apps\recognition\setupFMD.m
vlfeat-0.9.18\apps\recognition\setupGeneric.m
vlfeat-0.9.18\apps\recognition\setupScene67.m
vlfeat-0.9.18\apps\recognition\setupVoc.m
vlfeat-0.9.18\apps\recognition\trainEncoder.m
vlfeat-0.9.18\apps\recognition\traintest.m
vlfeat-0.9.18\apps\sift_mosaic.m
vlfeat-0.9.18\bin\glnx86\aib
vlfeat-0.9.18\bin\glnx86\libvl.so
vlfeat-0.9.18\bin\glnx86\mser
vlfeat-0.9.18\bin\glnx86\sift
vlfeat-0.9.18\bin\glnx86\test_gauss_elimination
vlfeat-0.9.18\bin\glnx86\test_getopt_long
vlfeat-0.9.18\bin\glnx86\test_gmm
vlfeat-0.9.18\bin\glnx86\test_heap-def
vlfeat-0.9.18\bin\glnx86\test_host
vlfeat-0.9.18\bin\glnx86\test_imopv
vlfeat-0.9.18\bin\glnx86\test_kmeans
vlfeat-0.9.18\bin\glnx86\test_liop
vlfeat-0.9.18\bin\glnx86\test_mathop
vlfeat-0.9.18\bin\glnx86\test_mathop_abs
vlfeat-0.9.18\bin\glnx86\test_nan
vlfeat-0.9.18\bin\glnx86\test_qsort-def
vlfeat-0.9.18\bin\glnx86\test_rand
vlfeat-0.9.18\bin\glnx86\test_sqrti
vlfeat-0.9.18\bin\glnx86\test_stringop
vlfeat-0.9.18\bin\glnx86\test_svd2
vlfeat-0.9.18\bin\glnx86\test_threads
vlfeat-0.9.18\bin\glnx86\test_vec_comp
vlfeat-0.9.18\bin\glnxa64\aib
vlfeat-0.9.18\bin\glnxa64\libvl.so
vlfeat-0.9.18\bin\glnxa64\mser
vlfeat-0.9.18\bin\glnxa64\sift
vlfeat-0.9.18\bin\glnxa64\test_gauss_elimination
vlfeat-0.9.18\bin\glnxa64\test_getopt_long
vlfeat-0.9.18\bin\glnxa64\test_gmm
vlfeat-0.9.18\bin\glnxa64\test_heap-def
vlfeat-0.9.18\bin\glnxa64\test_host
vlfeat-0.9.18\bin\glnxa64\test_imopv
vlfeat-0.9.18\bin\glnxa64\test_kmeans
vlfeat-0.9.18\bin\glnxa64\test_liop
vlfeat-0.9.18\bin\glnxa64\test_mathop
vlfeat-0.9.18\bin\glnxa64\test_mathop_abs
vlfeat-0.9.18\bin\glnxa64\test_nan
vlfeat-0.9.18\bin\glnxa64\test_qsort-def
vlfeat-0.9.18\bin\glnxa64\test_rand
vlfeat-0.9.18\bin\glnxa64\test_sqrti
vlfeat-0.9.18\bin\glnxa64\test_stringop
vlfeat-0.9.18\bin\glnxa64\test_svd2
vlfeat-0.9.18\bin\glnxa64\test_threads
vlfeat-0.9.18\bin\glnxa64\test_vec_comp
vlfeat-0.9.18\bin\maci\aib
vlfeat-0.9.18\bin\maci\libvl.dylib
vlfeat-0.9.18\bin\maci\mser
vlfeat-0.9.18\bin\maci\sift
vlfeat-0.9.18\bin\maci\test_gauss_elimination
vlfeat-0.9.18\bin\maci\test_getopt_long
vlfeat-0.9.18\bin\maci\test_gmm
vlfeat-0.9.18\bin\maci\test_heap-def
vlfeat-0.9.18\bin\maci\test_host
vlfeat-0.9.18\bin\maci\test_imopv
vlfeat-0.9.18\bin\maci\test_kmeans
vlfeat-0.9.18\bin\maci\test_liop
vlfeat-0.9.18\bin\maci\test_mathop
vlfeat-0.9.18\bin\maci\test_mathop_abs
vlfeat-0.9.18\bin\maci\test_nan
vlfeat-0.9.18\bin\maci\test_qsort-def
vlfeat-0.9.18\bin\maci\test_rand
vlfeat-0.9.18\bin\maci\test_sqrti
vlfeat-0.9.18\bin\maci\test_stringop
vlfeat-0.9.18\bin\maci\test_svd2
vlfeat-0.9.18\bin\maci\test_threads
vlfeat-0.9.18\bin\maci\test_vec_comp
vlfeat-0.9.18\bin\maci64\aib
vlfeat-0.9.18\bin\maci64\libvl.dylib
vlfeat-0.9.18\bin\maci64\mser
vlfeat-0.9.18\bin\maci64\sift
vlfeat-0.9.18\bin\maci64\test_gauss_elimination
vlfeat-0.9.18\bin\maci64\test_getopt_long
vlfeat-0.9.18\bin\maci64\test_gmm
vlfeat-0.9.18\bin\maci64\test_heap-def
vlfeat-0.9.18\bin\maci64\test_host
vlfeat-0.9.18\bin\maci64\test_imopv
vlfeat-0.9.18\bin\maci64\test_kmeans
vlfeat-0.9.18\bin\maci64\test_liop
vlfeat-0.9.18\bin\maci64\test_mathop
vlfeat-0.9.18\bin\maci64\test_mathop_abs
vlfeat-0.9.18\bin\maci64\test_nan
vlfeat-0.9.18\bin\maci64\test_qsort-def
vlfeat-0.9.18\bin\maci64\test_rand
vlfeat-0.9.18\bin\maci64\test_sqrti

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • Visual-C-MATLAB-image-processing
    本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章～第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章～第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章～第12章，是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。 本书附带的光盘给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。 本书讲解深入浅出，实例程序丰富，注重理论与实践相结合。本书可作为计算机应用、自动化、图像处理与模式识别、机电一体化专业的高年级本科生或研究生的参考书，也可供从事图像处理与识别的研究人员和工程技术人员阅读参考。(This book introduces the basic principles of image processing and recognition of the typical methods and practical skills . The book is divided into 12 chapters , Chapter 1- Chapter 6 is the basis of the content of image processing and recognition , including images scientific overview , MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition Chapter 7- Section Chapter 10 is a project example image processing and recognition , covering the medical image processing, character recognition and self- guided trolley path recognition example , the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers learn how to use MATLAB language fast simulation , debugging and estimation methods algorithm. Chapter 11- Chapter 12 , are two examples of highly integrated , namely Visual C++ implementation based on neural network character recognition system and a license plate positioning system. The book)
    2014-03-26 11:09:37下载
    积分：1
  • bianjieXY
    程序可以提取点云数据的特征点，提取三维散乱点云的边界(Program point cloud data can be extracted feature points extracted boundary of D Scattered Clouds)
    2013-09-09 20:55:05下载
    积分：1
  • MotionDetection
    说明：  静止背景下运动目标检测，采用帧间差分的方法进行运动目标识别(Static background motion detection, frame difference methods using Moving Object Recognition)
    2010-04-12 15:22:15下载
    积分：1
  • lyf
    利用图像的不变矩以及模式识别的内容，构造三维飞机图像的矩特征，然后再利用D-S证据理论的改进方法 吸收法对图像进行融合 对飞机的型号进行匹配(Moment invariant of image and pattern recognition of the content, structure features three-dimensional plane images of the moment, and then use the improved DS evidence theory method of absorption of the fusion images to match the type of aircraft)
    2021-05-13 14:30:03下载
    积分：1
  • gkde
    Gaussian Kernel Density Estimation with Bounded Support
    2008-05-22 20:15:32下载
    积分：1
  • CV1
    属于图像分割的一种，利用matlab实现CV型,可以当function使用。其中包含图片，可以进行使用。(It belongs to one kind of image segmentation, and uses MATLAB to realize CV type, which can be used as function.It contains pictures, which can be used.)
    2019-04-16 21:59:34下载
    积分：1
  • knnt
    knn分类器，是数字图像处理与处理中经常使用到的一种分类方法！(KNN Classifier is the digital image processing and handling are often used as a classification method!)
    2020-11-09 13:59:46下载
    积分：1
  • background
    实现帧差法求背景的matlab程序和示例图片(Frame-difference method to achieve the background image matlab procedures and sample)
    2009-05-04 20:06:07下载
    积分：1
  • gmm-cv
    OpenCV_基于混合高斯模型GMM的运动目标检测。内附监测监控视频，方便测试使用。(OpenCV_ GMM Gaussian mixture model based moving target detection. Included monitoring surveillance video, easy testing.)
    2014-02-26 14:47:48下载
    积分：1
  • gabor
    gabor特征提取程序，对于搞问纹理提取的人来说很有用处(gabor feature extraction process, engage in asking for the texture extraction is very useful for those who)
    2010-03-06 17:17:46下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！