opencv之运动目标动作分割

本文所需要了解的库函数有：

void cvAbsDiff( const CvArr* src1, const CvArr* src2, CvArr* dst );//计算两个数组差的绝对值

void cvUpdateMotionHistory( const CvArr* silhouette, CvArr* mhi,
                            double timestamp, double duration );去掉影像(silhouette) 以更新运动历史图像

void cvCalcMotionGradient( const CvArr* mhi, CvArr* mask, CvArr* orientation,
                           double delta1, double delta2, int aperture_size=3 );计算运动历史图像的梯度方向

CvSeq* cvSegmentMotion( const CvArr* mhi, CvArr* seg_mask, CvMemStorage* storage,
                        double timestamp, double seg_thresh );将整个运动分割为独立的运动部分，返回独立的CvConnectedComp运动部件

double cvCalcGlobalOrientation( const CvArr* orientation, const CvArr* mask, const CvArr* mhi,
                                double timestamp, double duration );计算某些选择区域的全局运动方向

double cvNorm( const CvArr* arr1, const CvArr* arr2=NULL, int norm_type=CV_L2, const CvArr* mask=NULL );//计算范数

如果 arr2 为空（NULL）

norm = ||arr1||C = maxI abs(arr1(I)), 如果 normType = CV_C

norm = ||arr1||L1 = sumI abs(arr1(I)), 如果 normType = CV_L1

norm = ||arr1||L2 = sqrt( sumI arr1(I)2), 如果 normType = CV_L2 

/* types of array norm */
#define CV_C            1
#define CV_L1           2
#define CV_L2           4
#define CV_NORM_MASK    7
#define CV_RELATIVE     8
#define CV_DIFF         16
#define CV_MINMAX       32


#define CV_DIFF_C       (CV_DIFF | CV_C)
#define CV_DIFF_L1      (CV_DIFF | CV_L1)
#define CV_DIFF_L2      (CV_DIFF | CV_L2)
#define CV_RELATIVE_C   (CV_RELATIVE | CV_C)
#define CV_RELATIVE_L1  (CV_RELATIVE | CV_L1)
#define CV_RELATIVE_L2  (CV_RELATIVE | CV_L2)

更多参考:http://www.opencv.org.cn/index.php/Cxcore%E6%95%B0%E7%BB%84%E6%93%8D%E4%BD%9C

对于上式，有个数学概念要明确：（范数）

当p取1，2，∞的时候分别是以下几种最简单的情形：

1-范数：║x║1=│x1│+│x2│+…+│xn│

2-范数：║x║2=（│x1│^2+│x2│^2+…+│xn│^2）^1/2

∞-范数：║x║∞=max（│x1│，│x2│，…，│xn│）

其中2-范数就是通常意义下的距离。

 

 

#pragma comment(lib,"cv.lib")
#pragma comment(lib,"cvaux.lib")
#pragma comment(lib,"highgui.lib")
#pragma comment(lib,"cxcore.lib")
#include<cv.h>
#include<highgui.h>
#include<stdio.h>
#include<time.h>
#include"Camer.h"

IplImage* frame;//原始图像
IplImage* dist;//最终的显示图像
IplImage* pre=NULL;//前一张图像
IplImage* gray;//灰度图
IplImage* diff;//差值图
IplImage *mhi = 0; // 运动历史图 
IplImage *orient = 0; // 方向图
IplImage *mask = 0; //掩码图
IplImage *segmask = 0; 
CvMemStorage* storage = 0; // 内存仓
const char* windowname= "演示";

void  Process( IplImage* img)
{
    double timestamp = (double)clock()/CLOCKS_PER_SEC; // get current time in seconds
    CvSize size = cvSize(img->width,img->height); // get current frame size
 
	cvCvtColor(img,gray,CV_BGR2GRAY);//灰度转换
	cvAbsDiff(gray,pre,diff);//计算差值
 	cvCopy( gray,pre);//拷贝数据 便于下次使用
    cvThreshold( diff, diff, 30, 1, CV_THRESH_BINARY ); // 二值化
    cvUpdateMotionHistory( diff, mhi, timestamp, 1 ); // 运动历史图

    // 转换MHI到8U
    cvCvtScale( mhi, mask, 255,(1 - timestamp)*255 );
    cvZero( dist );
    cvCvtPlaneToPix( mask, 0, 0, 0, dist );

    // 计算运动的方向图
    cvCalcMotionGradient( mhi, mask, orient, 0.5, 0.05, 3 );
 
	//分割运动到独立的部分
    cvClearMemStorage(storage);
    CvSeq *seq = cvSegmentMotion( mhi, segmask, storage, timestamp, 1 );

    //获取所有的运动组件
    for(int i = -1; i < seq->total; i++ ) {

		CvRect comp_rect;
		CvScalar color;
		double magnitude;
        if( i < 0 ) { // 整张图片的运动
            comp_rect = cvRect( 0, 0, size.width, size.height );
            color = CV_RGB(255,255,255);
            magnitude = 100;
        }
        else { //单独的运动部件
            comp_rect = ((CvConnectedComp*)cvGetSeqElem( seq, i ))->rect;
            if( comp_rect.width + comp_rect.height < 100 ) // reject very small components
                continue;
            color = CV_RGB(255,0,0);
            magnitude = 30;
        }

        //设置ROI
        cvSetImageROI( diff, comp_rect );
        cvSetImageROI( mhi, comp_rect );
        cvSetImageROI( orient, comp_rect );
        cvSetImageROI( mask, comp_rect );

        // 计算方向
        double angle = cvCalcGlobalOrientation( orient, mask, mhi, timestamp, 1);
        angle = 360.0 - angle;  // adjust for images with top-left origin
        double count = cvNorm( diff, 0, CV_L1, 0 ); // calculate number of points within silhouette ROI

		//重设ROI
        cvResetImageROI( mhi );
        cvResetImageROI( orient );
        cvResetImageROI( mask );
        cvResetImageROI( diff );

        // check for the case of little motion
        if( count < comp_rect.width*comp_rect.height * 0.05 )
            continue;

        // draw a clock with arrow indicating the direction
        CvPoint center = cvPoint( (comp_rect.x + comp_rect.width/2),
                          (comp_rect.y + comp_rect.height/2) );

        cvCircle( dist, center, cvRound(magnitude*1.2), color, 3, CV_AA, 0 );
        cvLine( dist, center, cvPoint( cvRound( center.x + magnitude*cos(angle*CV_PI/180)),
                cvRound( center.y - magnitude*sin(angle*CV_PI/180))), color, 3, CV_AA, 0 );
    }
}

 
 
int main()
{
	CCameraDS camer;
	camer.OpenCamera(0,false); //打开摄像头
	frame = camer.QueryFrame();
	if(frame==NULL)
	{
			return 1;
	}
	//创建相应的变量
    pre= cvCreateImage(cvGetSize(frame),IPL_DEPTH_8U,1); //创建前一张显示图像的存储空间
	dist = cvCreateImage(cvGetSize(frame),IPL_DEPTH_8U,3); //创建显示图像
	gray=cvCreateImage(cvGetSize(frame),IPL_DEPTH_8U,1);//灰度图像
 	diff=cvCreateImage(cvGetSize(frame),IPL_DEPTH_8U,1);//差值图像
    mhi = cvCreateImage( cvGetSize(frame), IPL_DEPTH_32F, 1 );
    orient = cvCreateImage( cvGetSize(frame), IPL_DEPTH_32F, 1 );
    segmask = cvCreateImage( cvGetSize(frame), IPL_DEPTH_32F, 1 );
    mask = cvCreateImage( cvGetSize(frame), IPL_DEPTH_8U, 1 );
 
	storage = cvCreateMemStorage(0);

	cvNamedWindow(windowname,1);

	while(true)
	{
		frame = camer.QueryFrame();
		if(!frame)
			break;
 
		Process(frame);//处理图像
	 	cvShowImage(windowname,dist);
		if(cvWaitKey(10)>=0) break;
	}
	cvReleaseImage(&dist);
	cvReleaseImage(&pre);
	cvReleaseImage(&gray);
	cvReleaseImage(&diff);
	cvReleaseImage(&mhi);
	cvReleaseImage(&orient);
	cvReleaseImage(&segmask);
	cvReleaseImage(&mask);
	cvReleaseMemStorage(&storage);
	cvDestroyWindow(windowname);
	return 0;
}