图像处理之其他杂项（一）之MeanShift的目标跟踪算法opencv c++代码 VS2015+opencv3.2

MeanShift的目标跟踪算法

　　这几天在学meanshift跟踪的原理和实现，虽然还不是特别明白，但总想先找个程序跑一下试一下效果，网上的程序多是基于c接口的老的opencv程序，在借鉴大神思路的基础上，对其代码进行了一些小的改动升级，变成了c++接口。大神‘taotao1233’的原meanshift讲解与源代码网址：http://blog.csdn.net/jinshengtao/article/details/30258833。

　　ps:虽然代码可用，但对于代码算法具体原理及实现还未掌握透彻，有待进一步学习。
　　1.这是根据原有作者的c接口opencv升级的c++接口程序,适用于opencv 接口2.0版本，开发环境为VS2015+opencv3.2。
　　2.程序视频的默认路径为”E\\dd4.mp4“。”
　　3.视频启动后按 s 键进行暂停，然后用鼠标选取需要跟踪的矩形框，再次按 s 视频启动进行跟踪。
　　4.程序有个bug，视频播放完毕会报错。
　　5.程序中有imwrite函数，opencv本身bug存在，建议编译时选择release选项。

//#include "stdafx.h"
//#include "cv.h"
//#include "highgui.h"
#include<opencv.hpp>
#define  u_char unsigned char
#define  DIST 0.5
#define  NUM 20
using namespace std;
using namespace cv;
//全局变量
bool pause = false;
bool is_tracking = false;
Rect drawing_box;
Mat current;
double *hist1, *hist2;
double *m_wei;
double C = 0.0;
bool xx = false;
bool g_bDrawingBox = false;
Mat tempImage;
void ShowHelpText();
void init_target(double *hist1, double *m_wei, Mat current)
{
int t_h, t_w, t_x, t_y;
double h, dist;
int i, j;
int q_r, q_g, q_b, q_temp;

t_h = drawing_box.height;
t_w = drawing_box.width;
t_x = drawing_box.x;
t_y = drawing_box.y;

h = pow(((double)t_w) / 2, 2) + pow(((double)t_h) / 2, 2);            //带宽
Mat pic_hist = Mat(300, 200, CV_8UC3);     //生成直方图图像

for (i = 0; i < t_w*t_h; i++)
{
m_wei[i] = 0.0;
}

for (i = 0; i < 4096; i++)
{
hist1[i] = 0.0;
}

for (i = 0; i < t_h; i++)
{
for (j = 0; j < t_w; j++)
{
dist = pow(i - (double)t_h / 2, 2) + pow(j - (double)t_w / 2, 2);
m_wei[i * t_w + j] = 1 - dist / h;
//printf("%f\n",m_wei[i * t_w + j]);
C += m_wei[i * t_w + j];
}
}

//计算目标权值直方
for (i = t_y; i < t_y + t_h; i++)
{
for (j = t_x; j < t_x + t_w; j++)
{
//rgb颜色空间量化为16*16*16 bins
/*q_r = ((u_char)current.at(i + j * 3 + 2) / 16;
q_g = ((u_char)current->imageData[i * current->widthStep + j * 3 + 1]) / 16;
q_b = ((u_char)current->imageData[i * current->widthStep + j * 3 + 0]) / 16;*/
q_r = current.at<Vec3b>(i, j)[2] / 16;
q_g = current.at<Vec3b>(i, j)[1] / 16;
q_b = current.at<Vec3b>(i, j)[0] / 16;
q_temp = q_r * 256 + q_g * 16 + q_b;
hist1[q_temp] = hist1[q_temp] + m_wei[(i - t_y) * t_w + (j - t_x)];
}
}

//归一化直方图
for (i = 0; i < 4096; i++)
{
hist1[i] = hist1[i] / C;
//printf("%f\n",hist1[i]);
}

//生成目标直方图
double temp_max = 0.0;

for (i = 0; i < 4096; i++)         //求直方图最大值，为了归一化
{
//printf("%f\n",val_hist[i]);
if (temp_max < hist1[i])
{
temp_max = hist1[i];
}
}
//画直方图
Point p1, p2;
double bin_width = pic_hist.cols / 4096;
double bin_unith = pic_hist.rows / temp_max;

for (i = 0; i < 4096; i++)
{
p1.x = i * bin_width;
p1.y = pic_hist.rows;
p2.x = (i + 1)*bin_width;
p2.y = pic_hist.rows - hist1[i] * bin_unith;
//printf("%d,%d,%d,%d\n",p1.x,p1.y,p2.x,p2.y);
rectangle(pic_hist, p1, p2, Scalar(0, 255, 0), -1, 8, 0);
}
imwrite("hist1.jpg", pic_hist);
//cvReleaseImage(&pic_hist);
}

void MeanShift_Tracking(Mat current)
{
int num = 0, i = 0, j = 0;
int t_w = 0, t_h = 0, t_x = 0, t_y = 0;
double *w = 0, *hist2 = 0;
double sum_w = 0, x1 = 0, x2 = 0, y1 = 2.0, y2 = 2.0;
int q_r, q_g, q_b;
int *q_temp;
//Mat pic_hist;

t_w = drawing_box.width;
t_h = drawing_box.height;

Mat pic_hist = Mat(300, 200, CV_8UC3);     //生成直方图图像
hist2 = (double *)malloc(sizeof(double) * 4096);
w = (double *)malloc(sizeof(double) * 4096);
q_temp = (int *)malloc(sizeof(int)*t_w*t_h);

while ((pow(y2, 2) + pow(y1, 2) > 0.5) && (num < NUM))
{
num++;
t_x = drawing_box.x;
t_y = drawing_box.y;
memset(q_temp, 0, sizeof(int)*t_w*t_h);
for (i = 0; i < 4096; i++)
{
w[i] = 0.0;
hist2[i] = 0.0;
}

for (i = t_y; i < t_h + t_y; i++)
{
for (j = t_x; j < t_w + t_x; j++)
{
//rgb颜色空间量化为16*16*16 bins
/*q_r = ((u_char)current->imageData[i * current->widthStep + j * 3 + 2]) / 16;
q_g = ((u_char)current->imageData[i * current->widthStep + j * 3 + 1]) / 16;
q_b = ((u_char)current->imageData[i * current->widthStep + j * 3 + 0]) / 16;*/
q_r = current.at<Vec3b>(i, j)[2] / 16;
q_g = current.at<Vec3b>(i, j)[1] / 16;
q_b = current.at<Vec3b>(i, j)[0] / 16;
q_temp[(i - t_y) *t_w + j - t_x] = q_r * 256 + q_g * 16 + q_b;
hist2[q_temp[(i - t_y) *t_w + j - t_x]] = hist2[q_temp[(i - t_y) *t_w + j - t_x]] + m_wei[(i - t_y) * t_w + j - t_x];
}
}

//归一化直方图
for (i = 0; i < 4096; i++)
{
hist2[i] = hist2[i] / C;
//printf("%f\n",hist2[i]);
}
//生成目标直方图
double temp_max = 0.0;

for (i = 0; i < 4096; i++)         //求直方图最大值，为了归一化
{
if (temp_max < hist2[i])
{
temp_max = hist2[i];
}
}
//画直方图
Point p1, p2;
double bin_width = pic_hist.cols / (4368);
double bin_unith = pic_hist.rows / temp_max;

for (i = 0; i < 4096; i++)
{
p1.x = i * bin_width;
p1.y = pic_hist.cols;
p2.x = (i + 1)*bin_width;
p2.y = pic_hist.rows - hist2[i] * bin_unith;
rectangle(pic_hist, p1, p2, Scalar(0, 255, 0), -1, 8, 0);
}
imwrite("hist2.jpg", pic_hist);

for (i = 0; i < 4096; i++)
{
if (hist2[i] != 0)
{
w[i] = sqrt(hist1[i] / hist2[i]);
}
else
{
w[i] = 0;
}
}

sum_w = 0.0;
x1 = 0.0;
x2 = 0.0;

for (i = 0; i < t_h; i++)
{
for (j = 0; j < t_w; j++)
{
//printf("%d\n",q_temp[i * t_w + j]);
sum_w = sum_w + w[q_temp[i * t_w + j]];
x1 = x1 + w[q_temp[i * t_w + j]] * (i - t_h / 2);
x2 = x2 + w[q_temp[i * t_w + j]] * (j - t_w / 2);
}
}
y1 = x1 / sum_w;
y2 = x2 / sum_w;

//中心点位置更新
drawing_box.x += y2;
drawing_box.y += y1;

}

rectangle(current, Point(drawing_box.x, drawing_box.y), Point(drawing_box.x + drawing_box.width, drawing_box.y + drawing_box.height), Scalar(255, 0, 0), 2);
imshow("Meanshift", current);
}

void onMouse(int eve
4000
nt, int x, int y, int flags, void *param)
{

if (pause)
{
switch (event)
{
case EVENT_MOUSEMOVE:
if (g_bDrawingBox)
{

drawing_box.width = x - drawing_box.x;
drawing_box.height = y - drawing_box.y;

}
break;
case CV_EVENT_LBUTTONDOWN:
g_bDrawingBox = true;
drawing_box = Rect(x, y, 0, 0);//记录起始点//the left up point of the rect
//drawing_box.x = x;
//drawing_box.y = y;

break;
case CV_EVENT_LBUTTONUP:
//finish drawing the rect (use color green for finish)
g_bDrawingBox = false;
xx = true;
drawing_box.width = x - drawing_box.x;
drawing_box.height = y - drawing_box.y;
rectangle(current, drawing_box.tl(), drawing_box.br(), Scalar(255, 0, 0), 2);

//目标初始化
hist1 = (double *)malloc(sizeof(double) * 16 * 16 * 16);
m_wei = (double *)malloc(sizeof(double)*drawing_box.height*drawing_box.width);
init_target(hist1, m_wei, current);
is_tracking = true;
//imshow("Meanshift", current);
break;
}
imshow("Meanshift", current);
return;
}
}

int main()
{

ShowHelpText();
VideoCapture capture("E://dd4.mp4");
capture.grab(); //从视频文件或捕获设备获取下一帧
capture.retrieve(current);//解码并返回抓取了的视频帧

while (1)
{

if (is_tracking)
{
MeanShift_Tracking(current);
}

int c = waitKey(1);
//暂停
if (c == 's')
{
while (1)
{
pause = true;
setMouseCallback("Meanshift", onMouse, 0);
current.copyTo(tempImage);
if (g_bDrawingBox)
rectangle(tempImage, drawing_box.tl(), drawing_box.br(), Scalar(255, 0, 0), 2);
if (xx == true)
break;
waitKey(2);
imshow("Meanshift", tempImage);
}
}

while (pause)
{
if (waitKey(0) == 's')
pause = false;
}
//if (current.size != 0)
try { imshow("Meanshift", current); }
catch (exception& e) { cout << "视频播放完毕"; return 0; }
//else
//break;
capture.grab(); //从视频文件或捕获设备获取下一帧
capture.retrieve(current);//解码并返回抓取了的视频帧
}

namedWindow("Meanshift", 1);
return 0;
}
void ShowHelpText()
{
//输出欢迎信息和OpenCV版本
printf("\n1.这是根据原有作者的c接口opencv升级的c++接口程序,适用于opencv2.0版本，开发环境为VS2015+opencv3.2\n");
printf("\n2.程序视频的默认路径为(E\\dd4.mp4)\n");
printf("\n3.视频启动后按 s 键进行暂停，然后用鼠标选取需要跟踪的矩形框，再次按 s 视频启动进行跟踪\n");
printf("\n4.程序有个bug，视频播放完毕会报错");
//printf("\n\n  ----------------------------------------------------------------------------\n");
//输出一些帮助信息
//printf("\n\n\n\t欢迎来到【鼠标交互演示】示例程序\n");
//printf("\n\n\t请在窗口中点击鼠标左键并拖动以绘制矩形\n");

}