//对运动物体的跟踪：
//如果背景固定,可用帧差法 然后在计算下连通域 将面积小的去掉即可
//如果背景单一,即你要跟踪的物体颜色和背景色有较大区别 可用基于颜色的跟踪 如CAMSHIFT 鲁棒性都是较好的
//如果背景复杂,如背景中有和前景一样的颜色 就需要用到一些具有预测性的算法 如卡尔曼滤波等 可以和CAMSHIFT结合
#ifdef _CH_
#pragma package <opencv>
#endif
#ifndef _EiC
#include "cv.h"
#include "highgui.h"
#include <stdio.h>
#include <ctype.h>
#endif
IplImage *image = 0, *hsv = 0, *hue = 0, *mask = 0, *backproject = 0, *histimg = 0;
//用HSV中的Hue分量进行跟踪
CvHistogram *hist = 0;
//直方图类
int backproject_mode = 0;
int select_object = 0;
int track_object = 0;
int show_hist = 1;
CvPoint origin;
CvRect selection;
CvRect track_window;
CvBox2D track_box;
//Meanshift跟踪算法返回的Box类
//typedef struct CvBox2D{
//CvPoint2D32f center; /* 盒子的中心 */
//CvSize2D32f size; /* 盒子的长和宽 */
//float angle; /* 水平轴与第一个边的夹角，用弧度表示*/
//}CvBox2D;
CvConnectedComp track_comp;
//连接部件
//typedef struct CvConnectedComp{
//double area; /* 连通域的面积 */
//float value; /* 分割域的灰度缩放值 */
//CvRect rect; /* 分割域的 ROI */
//} CvConnectedComp;
int hdims = 16;
//划分直方图bins的个数，越多越精确
float hranges_arr[] = { 0, 180 };
//像素值的范围
float* hranges = hranges_arr;
//用于初始化CvHistogram类
int vmin = 10, vmax = 256, smin = 30;
//用于设置滑动条
void on_mouse(int event, int x, int y, int flags, void* param)
//鼠标回调函数,该函数用鼠标进行跟踪目标的选择
{
if (!image)
return;
if (image->origin)
y = image->height - y;
//如果图像原点坐标在左下,则将其改为左上
if (select_object)
//select_object为1,表示在用鼠标进行目标选择
//此时对矩形类selection用当前的鼠标位置进行设置
{
selection.x = MIN(x, origin.x);
selection.y = MIN(y, origin.y);
selection.width = selection.x + CV_IABS(x - origin.x);
selection.height = selection.y + CV_IABS(y - origin.y);
selection.x = MAX(selection.x, 0);
selection.y = MAX(selection.y, 0);
selection.width = MIN(selection.width, image->width);
selection.height = MIN(selection.height, image->height);
selection.width -= selection.x;
selection.height -= selection.y;
}
switch (event)
{
case CV_EVENT_LBUTTONDOWN:
//鼠标按下,开始点击选择跟踪物体
origin = cvPoint(x, y);
selection = cvRect(x, y, 0, 0);
select_object = 1;
break;
case CV_EVENT_LBUTTONUP:
//鼠标松开,完成选择跟踪物体
select_object = 0;
if (selection.width > 0 && selection.height > 0)
//如果选择物体有效，则打开跟踪功能
track_object = -1;
break;
}
}
CvScalar hsv2rgb(float hue)
//用于将Hue量转换成RGB量
{
int rgb[3], p, sector;
static const int sector_data[][3] =
{ { 0, 2, 1 }, { 1, 2, 0 }, { 1, 0, 2 }, { 2, 0, 1 }, { 2, 1, 0 }, { 0, 1, 2 } };
hue *= 0.033333333333333333333333333333333f;
sector = cvFloor(hue);
p = cvRound(255 * (hue - sector));
p ^= sector & 1 ? 255 : 0;
rgb[sector_data[sector][0]] = 255;
rgb[sector_data[sector][1]] = 0;
rgb[sector_data[sector][2]] = p;
return cvScalar(rgb[2], rgb[1], rgb[0], 0);
}
int main(int argc, char** argv)
{
CvCapture* capture;
capture = cvCreateFileCapture("E:\\视频图片库\\bird4.mp4");// cvCaptureFromCAM(0);
// if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
// //打开摄像头
// capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );
// else if( argc == 2 )
// //打开avi
// capture = cvCaptureFromAVI( argv[1] );
if (!capture)
//打开视频流失败
{
fprintf(stderr, "Could not initialize capturing...\n");
return -1;
}
printf("Hot keys: \n"
"\tESC - quit the program\n"
"\tc - stop the tracking\n"
"\tb - switch to/from backprojection view\n"
"\th - show/hide object histogram\n"
"To initialize tracking, select the object with mouse\n");
//打印程序功能列表
cvNamedWindow("Histogram", 1);
//用于显示直方图
cvNamedWindow("CamShiftDemo", 0);
//用于显示视频
cvSetMouseCallback("CamShiftDemo", on_mouse, 0);
//设置鼠标回调函数
cvCreateTrackbar("Vmin", "CamShiftDemo", &vmin, 256, 0);
cvCreateTrackbar("Vmax", "CamShiftDemo", &vmax, 256, 0);
cvCreateTrackbar("Smin", "CamShiftDemo", &smin, 256, 0);
//设置滑动条
for (;;)
//进入视频帧处理主循环
{
IplImage* frame = 0;
int i, bin_w, c;
frame = cvQueryFrame(capture);
if (!frame)
break;
if (!image)
//image为0,表明刚开始还未对image操作过,先建立一些缓冲区
{
image = cvCreateImage(cvGetSize(frame), 8, 3);
image->origin = frame->origin;
hsv = cvCreateImage(cvGetSize(frame), 8, 3);
hue = cvCreateImage(cvGetSize(frame), 8, 1);
mask = cvCreateImage(cvGetSize(frame), 8, 1);
//分配掩膜图像空间
backproject = cvCreateImage(cvGetSize(frame), 8, 1);
//分配反向投影图空间,大小一样,单通道
hist = cvCreateHist(1, &hdims, CV_HIST_ARRAY, &hranges, 1);
//分配直方图空间
histimg = cvCreateImage(cvSize(320, 200), 8, 3);
//分配用于直方图显示的空间
cvZero(histimg);
//置背景为黑色
}
cvCopy(frame, image, 0);
cvCvtColor(image, hsv, CV_BGR2HSV);
//把图像从RGB表色系转为HSV表色系
if (track_object)
//track_object非零,表示有需要跟踪的物体
{
int _vmin = vmin, _vmax = vmax;
cvInRangeS(hsv, cvScalar(0, smin, MIN(_vmin, _vmax), 0),
cvScalar(180, 256, MAX(_vmin, _vmax), 0), mask);
//制作掩膜板，只处理像素值为H：0~180，S：smin~256，V：vmin~vmax之间的部分
cvSplit(hsv, hue, 0, 0, 0);
//分离H分量
if (track_object < 0)
//如果需要跟踪的物体还没有进行属性提取，则进行选取框类的图像属性提取
{
float max_val = 0.f;
cvSetImageROI(hue, selection);
//设置原选择框为ROI
cvSetImageROI(mask, selection);
//设置掩膜板选择框为ROI
cvCalcHist(&hue, hist, 0, mask);
//得到选择框内且满足掩膜板内的直方图
cvGetMinMaxHistValue(hist, 0, &max_val, 0, 0);
cvConvertScale(hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0);
// 对直方图的数值转为0~255
cvResetImageROI(hue);
//去除ROI
cvResetImageROI(mask);
//去除ROI
track_window = selection;
track_object = 1;
//置track_object为1,表明属性提取完成
cvZero(histimg);
bin_w = histimg->width / hdims;
for (i = 0; i < hdims; i++)
//画直方图到图像空间
{
int val = cvRound(cvGetReal1D(hist->bins, i)*histimg->height / 255);
CvScalar color = hsv2rgb(i*180.f / hdims);
cvRectangle(histimg, cvPoint(i*bin_w, histimg->height),
cvPoint((i + 1)*bin_w, histimg->height - val),
color, -1, 8, 0);
}
}
cvCalcBackProject(&hue, backproject, hist);
//计算hue的反向投影图
cvAnd(backproject, mask, backproject, 0);
//得到掩膜内的反向投影
cvCamShift(backproject, track_window,
cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1),
&track_comp, &track_box);
//使用MeanShift算法对backproject中的内容进行搜索,返回跟踪结果
track_window = track_comp.rect;
//得到跟踪结果的矩形框
if (backproject_mode)
cvCvtColor(backproject, image, CV_GRAY2BGR);
if (image->origin)
track_box.angle = -track_box.angle;
cvEllipseBox(image, track_box, CV_RGB(255, 0, 0), 3, CV_AA, 0);
//画出跟踪结果的位置
}
if (select_object && selection.width > 0 && selection.height > 0)
//如果正处于物体选择，画出选择框
{
cvSetImageROI(image, selection);
cvXorS(image, cvScalarAll(255), image, 0);
cvResetImageROI(image);
}
cvShowImage("CamShiftDemo", image);
cvShowImage("Histogram", histimg);
c = cvWaitKey(33);
if (c >= 0)
{
cvWaitKey(0);
}
//if ((char)c == 27)
// break;
switch ((char)c)
//按键切换功能
{
case 'b':
backproject_mode ^= 1;
break;
case 'c':
track_object = 0;
cvZero(histimg);
break;
case 'h':
show_hist ^= 1;
if (!show_hist)
cvDestroyWindow("Histogram");
else
cvNamedWindow("Histogram", 1);
break;
default:
;
}
}
cvReleaseCapture(&capture);
cvDestroyWindow("CamShiftDemo");
return 0;
}
#ifdef _EiC
main(1, "camshiftdemo.c");
#endif
这个就是书上的标准代码 框小 直接出错 我有测试视频 等我网盘链接
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楼主: 独乐乐
楼主
发表于 2016-6-22 01:08:34
