我的程序是用于对象跟踪。我可以对物体进行跟踪,并通过矩量法为物体x,y提供坐标。
输入图片描述
输入图片描述
我想在OpenCV2中将像素坐标转换为世界坐标。 我已经得到了旋转矩阵(3*3)和平移向量(3*1)通过相机校准,我知道我的相机的焦距。
现在,我定义如下:
CvMat *rotation = (CvMat*)cvLord("Rotation.xml")
CvMat *translation = (CvMat*)cvLord("Translation.xml")
这是我的程序的一部分。
void trackFilteredObject(Mat threshold,Mat HSV, Mat &Birds_image){
vector <Fruit> apples;
Mat temp;
threshold.copyTo(temp);
// these two vectors needed for output of findContours
vector< vector<Point> > contours;
vector<Vec4i> hierarchy;
// find contours of filtered image using OpenCv findCountours function
findContours(temp,contours,hierarchy,CV_RETR_CCOMP,CV_CHAIN_APPROX_SIMPLE );
// use moments method to find our filtered object.
double refArea = 0;
bool objectFound = false;
if (hierarchy.size() > 0) {
int numObjects = hierarchy.size();
// if number of objects greater than MAX_NUM_OBJECTS, we have a noisy filter.
if(numObjects<MAX_NUM_OBJECTS){
for (int index = 0; index >= 0; index = hierarchy[index][0]) {
Moments moment = moments((cv::Mat)contours[index]);
double area = moment.m00;
if(area>MIN_OBJECT_AREA){
Fruit apple;
// moments method
apple.setXPos(moment.m10/area);
apple.setYPos(moment.m01/area);
apples.push_back(apple);
objectFound = true;
}else objectFound = false;
}
if(objectFound ==true){
// draw object location on screen
drawObject(apples,Birds_image);
}
}else putText(Birds_image,"TOO MUCH NOISE! ADJUST FILTER",Point(0,50),1,2,Scalar(0,0,255),2);
}
}
drawObject(apples,Birds_image)是这样的
void drawObject(vector<Fruit> theFruits,Mat &frame){
for(int i =0; i<theFruits.size(); i++){
cv::circle(frame,cv::Point(theFruits.at(i).getXPos(),theFruits.at(i).getYPos()),10,cv::Scalar(0,0,255));
cv::putText(frame,intToString(theFruits.at(i).getXPos())+ " , " + intToString(theFruits.at(i).getYPos()),cv::Point(theFruits.at(i).getXPos(),theFruits.at(i).getYPos()+20),1,1,Scalar(0,255,0));
}
}
我使用这些尾文件和头文件。
Fruit.h
#pragma once
#include <string>
using namespace std;
class Fruit
{
public:
Fruit(void);
~Fruit(void);
int getXPos();
void setXPos(int x);
int getYPos();
void setYPos(int y);
private:
int xPos, yPos;
string type;
};
Fruit.cpp
#include "Fruit.h"
Fruit::Fruit(void)
{
}
Fruit::~Fruit(void)
{
}
int Fruit::getXPos(){
return Fruit::xPos;
}
void Fruit::setXPos(int x){
Fruit::xPos = x;
xPos = x;
}
int Fruit::getYPos(){
return Fruit::yPos;
}
void Fruit::setYPos(int y){
Fruit::yPos = y;
yPos = y;
}
你能告诉我你的好主意吗?
看看opencv中的findHomography函数。它有助于找到从一个平面到另一个平面的变换,但只能找到二维坐标。
此链接提供了将坐标从图像平面转换为对象平面的类似示例。(给定4个已知点,相机像素到平面世界点)