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OpenCV 使用光流法检测物体运动

2013-11-10 16:42 453 查看
OpenCV 可以使用光流法检测物体运动,贴上代码以及效果。

// opticalflow.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"

// Example 10-1. Pyramid Lucas-Kanade optical flow code
//
/* *************** License:**************************
Oct. 3, 2008
Right to use this code in any way you want without warrenty, support or any guarentee of it working.

BOOK: It would be nice if you cited it:
Learning OpenCV: Computer Vision with the OpenCV Library
by Gary Bradski and Adrian Kaehler
Published by O'Reilly Media, October 3, 2008

AVAILABLE AT: http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134 Or: http://oreilly.com/catalog/9780596516130/ ISBN-10: 0596516134 or: ISBN-13: 978-0596516130

OTHER OPENCV SITES:
* The source code is on sourceforge at: http://sourceforge.net/projects/opencvlibrary/ * The OpenCV wiki page (As of Oct 1, 2008 this is down for changing over servers, but should come back): http://opencvlibrary.sourceforge.net/ * An active user group is at: http://tech.groups.yahoo.com/group/OpenCV/ * The minutes of weekly OpenCV development meetings are at: http://pr.willowgarage.com/wiki/OpenCV ************************************************** */

#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);
CvSize      img_sz    = cvGetSize( imgA );
int         win_size = 10;
IplImage* imgC = cvLoadImage("OpticalFlow1.jpg",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, 1 );
IplImage* tmp_image = cvCreateImage( img_sz, IPL_DEPTH_32F, 1 );
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, 1 );
IplImage* pyrB = cvCreateImage( pyr_sz, IPL_DEPTH_32F, 1 );
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;
}


两张测试图片:

OpticalFlow0.jpg



OpticalFlow1.jpg



运行结果:

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