CT压缩追踪算法

绝对的可运行，配合usb摄像头，选定目标即可对目标进行实时跟踪，效果很好。

#include “CompressiveTracker.h“
#include 
#include 
using namespace cv;
using namespace std;

//------------------------------------------------
CompressiveTracker::CompressiveTracker（void）
{
	featureMinNumRect = 2;
	featureMaxNumRect = 4;	// number of rectangle from 2 to 4
	featureNum = 50;	// number of all weaker classifiers i.efeature pool
	rOuterPositive = 4;	// radical scope of positive samples
	rSearchWindow = 25; // size of search window
	muPositive = vector（featureNum 0.0f）;
	muNegative = vector（featureNum 0.0f）;
	sigmaPositive = vector（featureNum 1.0f）;
	sigmaNegative = vector（featureNum 1.0f）;
	learnRate = 0.85f;	// Learning rate parameter
}

CompressiveTracker::~CompressiveTracker（void）
{
}


//haar算法检测器
void CompressiveTracker::HaarFeature（Rect& _objectBox int _numFeature）
/*Description: 计算haar特征    
  参数:
  -_objectBox: [x y width height] object rectangle   目标矩形框
  -_numFeature: total number of features.The default is 50.
*/
{
	features = vector>（_numFeature vector（））;
	featuresWeight = vector>（_numFeature vector（））;
	
	int numRect;
	Rect rectTemp;
	float weightTemp;
      
	for （int i=0; i<_numFeature; i++）
	{
		numRect = cvFloor（rng.uniform（（double）featureMinNumRect （double）featureMaxNumRect））;
	    
		//int c = 1;
		for （int j=0; j		{
			
			rectTemp.x = cvFloor（rng.uniform（0.0 （double）（_objectBox.width - 3）））;
			rectTemp.y = cvFloor（rng.uniform（0.0 （double）（_objectBox.height - 3）））;
			rectTemp.width = cvCeil（rng.uniform（0.0 （double）（_objectBox.width - rectTemp.x - 2）））;
			rectTemp.height = cvCeil（rng.uniform（0.0 （double）（_objectBox.height - rectTemp.y - 2）））;
			features[i].push_back（rectTemp）;

			weightTemp = （float）pow（-1.0 cvFloor（rng.uniform（0.0 2.0））） / sqrt（float（numRect））;
            //weightTemp = （float）pow（-1.0 c）;
			
			featuresWeight[i].push_back（weightTemp）;
           
		}
	}
}


void CompressiveTracker::sampleRect（Mat& _image Rect& _objectBox float _rInner float _rOuter int _maxSampleNum vector& _sampleBox）
/* Description: compute the coordinate of positive and negative sample image templates
   Arguments:
   -_image:        processing frame
   -_objectBox:    recent object position 
   -_rInner:       inner sampling radius
   -_rOuter:       Outer sampling radius
   -_maxSampleNum: maximal number of sampled images
   -_sampleBox:    Storing the rectangle coordinates of the sampled images.
*/
{
	int rowsz = _image.rows - _objectBox.height - 1;
	int colsz = _image.cols - _objectBox.width - 1;
	float inradsq = _rInner*_rInner;
	float outradsq = _rOuter*_rOuter;

  	
	int dist;

	int minrow = max（0（int）_objectBox.y-（int）_rInner）;
	int maxrow = min（（int）rowsz-1（int）_objectBox.y+（int）_rInner）;
	int mincol = max（0（int）_objectBox.x-（int）_rInner）;
	int maxcol = min（（int）colsz-1（int）_objectBox.x+（int）_

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----

     文件       9198  2012-05-01 14:45  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracker.cpp

     文件       2163  2012-08-23 17:59  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracker.h

     文件       4005  2012-08-07 09:59  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracking.vcproj

     文件       1449  2012-08-24 10:47  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracking.vcproj.HP98402794308.Administrator.user

     文件       1427  2012-08-24 13:46  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracking.vcproj.PC-201008102047.Administrator.user

     文件       4540  2012-05-01 21:21  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracking.vcxproj

     文件       1168  2012-04-27 11:07  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracking.vcxproj.filters

     文件        143  2012-04-27 11:06  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\CompressiveTracking.vcxproj.user

     文件     962560  2011-12-04 05:39  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\david.mpg

     文件         12  2012-08-07 14:56  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\init.txt

     文件       1454  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\cl.command.1.tlog

     文件      25986  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\CL.read.1.tlog

     文件       1442  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\CL.write.1.tlog

     文件    1136877  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\CompressiveTracker.obj

     文件        381  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\CompressiveTracking.exe.intermediate.manifest

     文件         87  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\CompressiveTracking.lastbuildstate

     文件       3820  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\CompressiveTracking.log

     文件       1902  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\link.command.1.tlog

     文件       3234  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\link.read.1.tlog

     文件        956  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\link.write.1.tlog

     文件        616  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\mt.command.1.tlog

     文件       1044  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\mt.read.1.tlog

     文件        412  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\mt.write.1.tlog

     文件    1015000  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\RunTracker.obj

     文件     479232  2012-05-05 09:40  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\Release\vc100.pdb

     文件       4334  2012-05-05 09:39  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking\RunTracker.cpp

     文件    9440256  2012-08-24 13:46  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking.ncb

     文件   11685888  2012-05-05 13:19  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking.sdf

     文件        924  2012-04-27 11:07  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking.sln

     文件        923  2012-08-24 10:43  压缩TLD追踪方法\CTFromCam_v0\CompressiveTracking.sln.old

............此处省略23个文件信息