OpenCV的 - 如何计算从相机和速度哈尔级联分类器移动物体的距离？

Question

我工作的opencv的项目，我使用C ++。我被困在计算运动物体的距离和速度。

---

Problem:

I have detected moving cars in video using Haar classifier in Opencv.
But didn't find any way to calculate moving objects
distance from camera as well as moving objects speed. 
I want to achieve this using only 1 Camera. I am not using Stereo vision. 

这里是我的代码：

#include <stdio.h>
#include <opencv/cv.h>
#include <opencv/highgui.h>

CvHaarClassifierCascade *cascade;
CvMemStorage            *storage;

void detect(IplImage *img);

int main(int argc, char** argv)
{
  CvCapture *capture;
  IplImage  *frame;
  int input_resize_percent = 100;

  if(argc < 3)
  {
    std::cout << "Usage " << argv[0] << " cascade.xml video.avi" << std::endl;
    return 0;
  }

  if(argc == 4)
  {
    input_resize_percent = atoi(argv[3]);
    std::cout << "Resizing to: " << input_resize_percent << "%" << std::endl;
  }

  cascade = (CvHaarClassifierCascade*) cvLoad(argv[1], 0, 0, 0);
  storage = cvCreateMemStorage(0);
  capture = cvCaptureFromAVI(argv[2]);

  assert(cascade && storage && capture);

  cvNamedWindow("video", 1);

  IplImage* frame1 = cvQueryFrame(capture);
  frame = cvCreateImage(cvSize((int)((frame1->width*input_resize_percent)/100) , (int)((frame1->height*input_resize_percent)/100)), frame1->depth, frame1->nChannels);

  const int KEY_SPACE  = 32;
  const int KEY_ESC    = 27;

  int key = 0;
  do
  {
    frame1 = cvQueryFrame(capture);

    if(!frame1)
      break;

    cvResize(frame1, frame);

    detect(frame);

    key = cvWaitKey(10);

    if(key == KEY_SPACE)
      key = cvWaitKey(0);

    if(key == KEY_ESC)
      break;

  }while(1);

  cvDestroyAllWindows();
  cvReleaseImage(&frame);
  cvReleaseCapture(&capture);
  cvReleaseHaarClassifierCascade(&cascade);
  cvReleaseMemStorage(&storage);

  return 0;
}

void detect(IplImage *img)
{
  CvSize img_size = cvGetSize(img);
  CvSeq *object = cvHaarDetectObjects(
    img,
    cascade,
    storage,
    1.1, //1.1,//1.5, //-------------------SCALE FACTOR
    1, //2        //------------------MIN NEIGHBOURS
    0, //CV_HAAR_DO_CANNY_PRUNING
    cvSize(0,0),//cvSize( 30,30), // ------MINSIZE
    img_size //cvSize(70,70)//cvSize(640,480)  //---------MAXSIZE
    );

  std::cout << "Total: " << object->total << " cars" << std::endl;
  for(int i = 0 ; i < ( object ? object->total : 0 ) ; i++)
  {
    CvRect *r = (CvRect*)cvGetSeqElem(object, i);
    cvRectangle(img,
      cvPoint(r->x, r->y),
      cvPoint(r->x + r->width, r->y + r->height),
      CV_RGB(255, 0, 0), 2, 8, 0);
  }

  cvShowImage("video", img);
}

如果您有任何例子请提供更好的理解。它的赞赏。

谢谢

Answer 1

我怀疑的准确性，但下面提到的方法可以帮助你找到在一定程度上物体（移动）的距离。

• 脚步：
• 找到合适的网络养活你的帧识别视频中的物体。
• 获得检测的坐标，也许我们能找到的检测长度/面积进一步。
• 做这一切之前，找到摄像机放置在已知的距离已知大小的物体的焦距。（参见阿德里安pyimagesearch网站）。
• 与已知的焦距，并且已知大小的移动物体中，我们可以找到该对象的距离，同时在与检测到的帧的区域中的改变而移动。