视频稳定

Question

我正在研究视频稳定领域。我使用 OpenCV 实现了一个应用程序。

我的进步，例如：

冲浪点提取

匹配

估计刚性变换

翘曲仿射

但结果视频并不稳定。任何人都可以帮助我解决这个问题或为我提供一些源代码链接来改进吗？

示例视频：河马视频

这是我的代码 [编辑]

#include "stdafx.h"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <opencv2/nonfree/features2d.hpp>
#include <opencv2/opencv.hpp>
const double smooth_level = 0.7;
using namespace cv;
using namespace std;
struct TransformParam
{
    TransformParam() {}
    TransformParam(double _dx, double _dy, double _da) {
    dx = _dx;
    dy = _dy;
    da = _da;
}
   double dx; // translation x
   double dy; // translation y
   double da; // angle
};
int main( int argc, char** argv )
{
     VideoCapture cap ("test12.avi");  
     Mat cur, cur_grey;
     Mat prev, prev_grey;

     cap >> prev;
     cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
     // Step 1 - Get previous to current frame transformation (dx, dy, da) for all frames
     vector <TransformParam> prev_to_cur_transform; // previous to current
     int k=1;
     int max_frames =  cap.get(CV_CAP_PROP_FRAME_COUNT);
     VideoWriter writeVideo ("stable.avi",0,30,cvSize(prev.cols,prev.rows),true);
     Mat last_T;
     double avg_dx = 0, avg_dy = 0, avg_da = 0;
     Mat smooth_T(2,3,CV_64F);
     while(true) {
        cap >> cur;
        if(cur.data == NULL) {
           break;
        }
        cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
        // vector from prev to cur
        vector <Point2f> prev_corner, cur_corner;
        vector <Point2f> prev_corner2, cur_corner2;
        vector <uchar> status;
        vector <float> err;
        goodFeaturesToTrack(prev_grey, prev_corner, 200, 0.01, 30);
        calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err);
       // weed out bad matches
       for(size_t i=0; i < status.size(); i++) {
           if(status[i]) {
               prev_corner2.push_back(prev_corner[i]);
              cur_corner2.push_back(cur_corner[i]);
           }
       }
       // translation + rotation only
       Mat T = estimateRigidTransform(prev_corner2, cur_corner2, false); 
       // in rare cases no transform is found. We'll just use the last known good transform.
       if(T.data == NULL) {
          last_T.copyTo(T);
       }
       T.copyTo(last_T);
      // decompose T
      double dx = T.at<double>(0,2);
      double dy = T.at<double>(1,2);
      double da = atan2(T.at<double>(1,0), T.at<double>(0,0));
      prev_to_cur_transform.push_back(TransformParam(dx, dy, da));
      avg_dx = (avg_dx * smooth_level) + (dx * (1- smooth_level));
      avg_dy = (avg_dy * smooth_level) + (dy * (1- smooth_level));
      avg_da = (avg_da * smooth_level) + (da * (1- smooth_level));
      smooth_T.at<double>(0,0) = cos(avg_da);
      smooth_T.at<double>(0,1) = -sin(avg_da);
      smooth_T.at<double>(1,0) = sin(avg_da);
      smooth_T.at<double>(1,1) = cos(avg_da);
      smooth_T.at<double>(0,2) = avg_dx;
      smooth_T.at<double>(1,2) = avg_dy;
      Mat stable;
      warpAffine(prev,stable,smooth_T,prev.size());
      Mat canvas = Mat::zeros(cur.rows, cur.cols*2+10, cur.type());
      prev.copyTo(canvas(Range::all(), Range(0, prev.cols)));
      stable.copyTo(canvas(Range::all(), Range(prev.cols+10, prev.cols*2+10)));
      imshow("before and after", canvas);
      waitKey(20);
      writeVideo.write(stable);
      cur.copyTo(prev);
      cur_grey.copyTo(prev_grey);
      k++;
   }
 }

Answer 1

首先，你可以模糊你的图像。它会有所帮助。其次，您可以通过最简单的指数平滑 A（t+1） = a*A（t）+（1-a）*A（t+1） 的实现来轻松平滑矩阵，并使用 [0;1] 范围内的 a 值。 第三，您可以关闭某些类型的转换，例如旋转，移位等。下面是代码示例：

t = estimateRigidTransform(new, old, 0); // 0 means not all transformations (5 of 6)
if(!t.empty()){
//  t(Range(0,2), Range(0,2)) = Mat::eye(2, 2, CV_64FC1); // turning off rotation
//  t.at<double>(0,2) = 0; t.at<double>(1,2) = 0; // turning off shift dx and dy
    tAvrg = tAvrg*a + t*(1-a); // a - smooth level in [0;1] range, play with it
    warpAffine(new, stable, tAvrg, Size(new.cols, new.rows));
}