光流法 HS与LK

1、HS算法

#include "cv.h"#include "highgui.h"#include <math.h>#include <stdio.h>#include "opencv2/legacy/legacy.hpp"#define CVX_GRAY50 cvScalar(100)#define CVX_WHITE  cvScalar(255)int main(int argc, char** argv){    // Initialize, load two images from the file system, and    // allocate the images and other structures we will need for    // results.    // exit if no input images IplImage *imgA = 0, *imgB = 0;    //imgA = cvLoadImage("OpticalFlow0.jpg",0);    //imgB = cvLoadImage("OpticalFlow1.jpg",0);    //if(!(imgA)||!(imgB)){ printf("One of OpticalFlow0.jpg and/or OpticalFlow1.jpg didn't load\n"); return -1;}imgA = cvLoadImage("OpticalFlow0.jpg",0);    imgB = cvLoadImage("OpticalFlow1.jpg",0);    if(!(imgA)||!(imgB)){ printf("One of OpticalFlow0.jpg and/or OpticalFlow1.jpg didn't load\n"); return -1;}    IplImage* velx = cvCreateImage(cvGetSize(imgA),IPL_DEPTH_32F,1);    IplImage* vely = cvCreateImage(cvGetSize(imgA),IPL_DEPTH_32F,1);    IplImage* imgC = cvCreateImage(cvGetSize(imgA),IPL_DEPTH_8U,3);    cvNamedWindow( "OpticalFlow0" );    cvNamedWindow( "OpticalFlow1" );    cvNamedWindow( "Flow Results" );    cvShowImage( "OpticalFlow0",imgA );    cvShowImage( "OpticalFlow1",imgB );    // Call the actual Horn and Schunck algorithm    //    cvCalcOpticalFlowHS(         imgA,         imgB,         0,        velx,        vely,        .10,        cvTermCriteria(             CV_TERMCRIT_ITER | CV_TERMCRIT_EPS,            imgA->width,            1e-6        )    );    // Now make some image of what we are looking at:    //    cvZero( imgC );    int step = 4;    for( int y=0; y<imgC->height; y += step ) {        float* px = (float*) ( velx->imageData + y * velx->widthStep );        float* py = (float*) ( vely->imageData + y * vely->widthStep );        for( int x=0; x<imgC->width; x += step ) {            if( px[x]>1 && py[x]>1 ) {                cvCircle(                    imgC,                    cvPoint( x, y ),                    2,                    CVX_GRAY50,                    -1                );                cvLine(                    imgC,                    cvPoint( x, y ),                    cvPoint( x+px[x]/2, y+py[x]/2 ),                    CV_RGB(255,0,0),                    1,                    0                );            }        }    }    // show tracking    cvShowImage( "Flow Results",imgC );        cvWaitKey(0);    // destroy windows    cvDestroyWindow( "OpticalFlow0" );    cvDestroyWindow( "OpticalFlow1" );    cvDestroyWindow( "Flow Results" );    // release memory    cvReleaseImage( &imgA );    cvReleaseImage( &imgB );    cvReleaseImage( &imgC );    return 0;}

2、LK算法

#include "cv.h"#include "cxcore.h"#include "highgui.h"#include "stdio.h"const int MAX_CORNERS = 500;int main(int argc, char** argv) {   // Initialize, load two images from the file system, and   // allocate the images and other structures we will need for   // results.//IplImage* imgA = cvLoadImage("OpticalFlow0.jpg",CV_LOAD_IMAGE_GRAYSCALE);//IplImage* imgB = cvLoadImage("OpticalFlow1.jpg",CV_LOAD_IMAGE_GRAYSCALE);IplImage* imgA = cvLoadImage("3.jpg",CV_LOAD_IMAGE_GRAYSCALE);IplImage* imgB = cvLoadImage("4.jpg",CV_LOAD_IMAGE_GRAYSCALE);//IplImage* imgA = cvLoadImage("10.png",CV_LOAD_IMAGE_GRAYSCALE);//IplImage* imgB = cvLoadImage("11.png",CV_LOAD_IMAGE_GRAYSCALE);CvSize      img_sz    = cvGetSize( imgA );int         win_size = 10;//IplImage* imgC = cvLoadImage("OpticalFlow1.jpg",CV_LOAD_IMAGE_UNCHANGED);IplImage* imgC = cvLoadImage("4.jpg",CV_LOAD_IMAGE_UNCHANGED);//IplImage* imgC = cvLoadImage("11.png",CV_LOAD_IMAGE_UNCHANGED);// The first thing we need to do is get the features// we want to track.//IplImage* eig_image = cvCreateImage( img_sz, IPL_DEPTH_32F, 3 );IplImage* tmp_image = cvCreateImage( img_sz, IPL_DEPTH_32F, 3 );int              corner_count = MAX_CORNERS;CvPoint2D32f* cornersA        = new CvPoint2D32f[ MAX_CORNERS ];cvGoodFeaturesToTrack(imgA,eig_image,tmp_image,cornersA,&corner_count,0.01,5.0,0,3,0,0.04);cvFindCornerSubPix(imgA,cornersA,corner_count,cvSize(win_size,win_size),cvSize(-1,-1),cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,0.03));// Call the Lucas Kanade algorithm//char features_found[ MAX_CORNERS ];float feature_errors[ MAX_CORNERS ];CvSize pyr_sz = cvSize( imgA->width+8, imgB->height/3 );IplImage* pyrA = cvCreateImage( pyr_sz, IPL_DEPTH_32F,3 );    IplImage* pyrB = cvCreateImage( pyr_sz, IPL_DEPTH_32F,3 );  CvPoint2D32f* cornersB        = new CvPoint2D32f[ MAX_CORNERS ];  cvCalcOpticalFlowPyrLK(     imgA,     imgB,     pyrA,     pyrB,     cornersA,     cornersB,     corner_count,     cvSize( win_size,win_size ),     5,     features_found,     feature_errors,     cvTermCriteria( CV_TERMCRIT_ITER | CV_TERMCRIT_EPS, 20, .3 ),     0  );  // Now make some image of what we are looking at:  //  for( int i=0; i<corner_count; i++ ) {     if( features_found[i]==0|| feature_errors[i]>550 ) { //       printf("Error is %f/n",feature_errors[i]);        continue;     } //    printf("Got it/n");     CvPoint p0 = cvPoint(        cvRound( cornersA[i].x ),        cvRound( cornersA[i].y )     );     CvPoint p1 = cvPoint(        cvRound( cornersB[i].x ),        cvRound( cornersB[i].y )     );     cvLine( imgC, p0, p1, CV_RGB(255,0,0),2 );  }  cvNamedWindow("ImageA",0);  cvNamedWindow("ImageB",0);  cvNamedWindow("LKpyr_OpticalFlow",0);  cvShowImage("ImageA",imgA);  cvShowImage("ImageB",imgB);  cvShowImage("LKpyr_OpticalFlow",imgC);  cvWaitKey(0);  return 0;}