OpenCV - Stitching Images from a grid of images

Question

I have found some basic working examples on stitching via OpenCV for panoramic images. I have also found some useful documentation in the API docs, but I can't find out how to speed up the processing by providing additional information.

In my case, I generate a set of images in a 20x20 grid of individual frames, for a total of 400 images to be stitched into a single large one. This takes an enormous amount of time on a modern PC, so it would likely take hours on a developer board.

Is there any way to tell the OpenCV instance information about the images, such as me knowing in advance the relative positioning of all the images as they would appear on a grid? The only API calls I see so far is to just add all the images indiscriminately to a queue via vImg.push_back().

---

References

1. Stitching. Image Stitching - OpenCV API Documentation, Accessed 2014-02-26, <http://docs.opencv.org/modules/stitching/doc/stitching.html>
2. OpenCV Stitching example (Stitcher class, Panorama), Accessed 2014-02-26, <http://feelmare.blogspot.ca/2013/11/opencv-stitching-example-stitcher-class.html>
3. Panorama – Image Stitching in OpenCV, Accessed 2014-02-26, <http://ramsrigoutham.com/2012/11/22/panorama-image-stitching-in-opencv/>

Answer 1

I did some work with the stitching pipeline and though I do not consider myself an expert on the field, I did get better performance (and better results as well) adjusting each step of the pipeline separately. As you can see in the picture, the Stitching class is nothing but a wrapper of this pipeline:

Some interesting parts you can adjust are the resizing steps (there comes a point were more resolution just means more computation time and more inaccurate features), the matching process and (though this is just a guess) giving a good camera parameters instead of performing an estimation. This involves getting the camera parameters before doing the stitching, but it is not really hard. Here you have some reference: OpenCV Camera Calibration and 3D Reconstruction.

Again: I am not an expert, this is just based on my experience as an intern doing some experiments with the library!

Answer 2

So far as I know, there is no means to provide additional data to the OpenCV engine beyond just giving it a list of images. It does a pretty good job on its own though. I would check out some of the example code, and test how long each stitching operation takes. From my experiments using 4x6, 4x8, ..., 4x20 panoramic reconstructions, the CPU time required seems to increase with the number of overlapping images. I would imagine your case would require at least a minute to compute on a modern machine.

Source: https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/cpp/stitching.cpp?rev=6682

1   /*M///////////////////////////////////////////////////////////////////////////////////////
2   //
3   //  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4   //
5   //  By downloading, copying, installing or using the software you agree to this license.
6   //  If you do not agree to this license, do not download, install,
7   //  copy or use the software.
8   //
9   //
10  //                          License Agreement
11  //                For Open Source Computer Vision Library
12  //
13  // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
14  // Copyright (C) 2009, Willow Garage Inc., all rights reserved.
15  // Third party copyrights are property of their respective owners.
16  //
17  // Redistribution and use in source and binary forms, with or without modification,
18  // are permitted provided that the following conditions are met:
19  //
20  //   * Redistribution's of source code must retain the above copyright notice,
21  //     this list of conditions and the following disclaimer.
22  //
23  //   * Redistribution's in binary form must reproduce the above copyright notice,
24  //     this list of conditions and the following disclaimer in the documentation
25  //     and/or other materials provided with the distribution.
26  //
27  //   * The name of the copyright holders may not be used to endorse or promote products
28  //     derived from this software without specific prior written permission.
29  //
30  // This software is provided by the copyright holders and contributors "as is" and
31  // any express or implied warranties, including, but not limited to, the implied
32  // warranties of merchantability and fitness for a particular purpose are disclaimed.
33  // In no event shall the Intel Corporation or contributors be liable for any direct,
34  // indirect, incidental, special, exemplary, or consequential damages
35  // (including, but not limited to, procurement of substitute goods or services;
36  // loss of use, data, or profits; or business interruption) however caused
37  // and on any theory of liability, whether in contract, strict liability,
38  // or tort (including negligence or otherwise) arising in any way out of
39  // the use of this software, even if advised of the possibility of such damage.
40  //
41  //M*/
42  
43  // We follow to these papers:
44  // 1) Construction of panoramic mosaics with global and local alignment.
45  //    Heung-Yeung Shum and Richard Szeliski. 2000.
46  // 2) Eliminating Ghosting and Exposure Artifacts in Image Mosaics.
47  //    Matthew Uyttendaele, Ashley Eden and Richard Szeliski. 2001.
48  // 3) Automatic Panoramic Image Stitching using Invariant Features.
49  //    Matthew Brown and David G. Lowe. 2007.
50  
51  #include <iostream>
52  #include <fstream>
53  #include "opencv2/highgui/highgui.hpp"
54  #include "opencv2/stitching/stitcher.hpp"
55  
56  using namespace std;
57  using namespace cv;
58  
59  void printUsage()
60  {
61      cout <<
62          "Rotation model images stitcher.\n\n"
63          "stitching img1 img2 [...imgN]\n\n"
64          "Flags:\n"
65          "  --try_use_gpu (yes|no)\n"
66          "      Try to use GPU. The default value is 'no'. All default values\n"
67          "      are for CPU mode.\n"
68          "  --output <result_img>\n"
69          "      The default is 'result.jpg'.\n";
70  }
71  
72  bool try_use_gpu = false;
73  vector<Mat> imgs;
74  string result_name = "result.jpg";
75  
76  int parseCmdArgs(int argc, char** argv)
77  {
78      if (argc == 1)
79      {
80          printUsage();
81          return -1;
82      }
83      for (int i = 1; i < argc; ++i)
84      {
85          if (string(argv[i]) == "--help" || string(argv[i]) == "/?")
86          {
87              printUsage();
88              return -1;
89          }
90          else if (string(argv[i]) == "--try_gpu")
91          {
92              if (string(argv[i + 1]) == "no")
93                  try_use_gpu = false;
94              else if (string(argv[i + 1]) == "yes")
95                  try_use_gpu = true;
96              else
97              {
98                  cout << "Bad --try_use_gpu flag value\n";
99                  return -1;
100             }
101             i++;
102         }
103         else if (string(argv[i]) == "--output")
104         {
105             result_name = argv[i + 1];
106             i++;
107         }
108         else
109         {
110             Mat img = imread(argv[i]);
111             if (img.empty())
112             {
113                 cout << "Can't read image '" << argv[i] << "'\n";
114                 return -1;
115             }
116             imgs.push_back(img);
117         }
118     }
119     return 0;
120 }
121 
122 
123 int main(int argc, char* argv[])
124 {
125     int retval = parseCmdArgs(argc, argv);
126     if (retval) return -1;
127 
128     Mat pano;
129     Stitcher stitcher = Stitcher::createDefault(try_use_gpu);
130     Stitcher::Status status = stitcher.stitch(imgs, pano);
131 
132     if (status != Stitcher::OK)
133     {
134         cout << "Can't stitch images, error code = " << status << endl;
135         return -1;
136     }
137 
138     imwrite(result_name, pano);
139     return 0;
140 }
141 
142