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meanshift实现视频中动态目标的跟踪

meanshift

c++

opencv

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使用meanshift算法实现视频中动态目标的跟踪，适用于目标及背景灰度差异较大的场景。

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//#include "stdafx.h"

#include "cv.h"

#include "highgui.h"

#dene u_char unsigned char

#dene DIST 0.5

#dene NUM 20

//全局变量

bool pause = false;

bool is_tracking = false;

CvRect drawing_box;

IplImage *current;

double *hist1, *hist2;

double *m_wei;

double C = 0.0;

void init_target(double *hist1, double *m_wei, IplImage *current)

{

IplImage *pic_hist = 0;

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;

//pow 函数是求每个矩阵元素 src(I) 的 p 次幂 dst[I] = src(I)p

h = pow(((double)t_w) / 2, 2) + pow(((double)t_h) / 2, 2); //带宽

pic_hist = cvCreateImage(cvSize(300, 200), IPL_DEPTH_8U, 3); //生成直方图图像

//初始化权值矩阵和目标直方图

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;

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->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_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;

}

//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 < hist1[i])

{

temp_max = hist1[i];

}

//画直方图

CvPoint p1, p2;

double bin_width = (double)pic_hist->width / 4096;

double bin_unith = (double)pic_hist->height / temp_max;

for (i = 0; i < 4096; i++)

{

p1.x = i * bin_width;

p1.y = pic_hist->height;

p2.x = (i + 1)*bin_width;

p2.y = pic_hist->height - hist1[i] * bin_unith;

cvRectangle(pic_hist, p1, p2, cvScalar(0, 255, 0), -1, 8, 0);

}

cvSaveImage("hist1.jpg", pic_hist);

cvReleaseImage(&pic_hist);

}

void MeanShift_Tracking(IplImage *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;

IplImage *pic_hist = 0;

t_w = drawing_box.width;

t_h = drawing_box.height;

pic_hist = cvCreateImage(cvSize(300, 200), IPL_DEPTH_8U, 3);

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))

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