Question

我找到了一些关于通过OpenCV缝合全景图像的基本工作示例。我还在API docs中找到了一些有用的文档，但是我无法通过提供其他信息来了解如何加快处理速度。

在我的情况下，我在20x20网格的单个帧中生成一组图像，总共400个图像被拼接成一个大的图像。这需要在现代PC上花费大量时间，因此在开发板上可能需要数小时。

有没有办法告诉OpenCV实例有关图像的信息，比如我事先知道所有图像在网格上的相对位置？到目前为止，我看到的唯一API调用是通过vImg.push_back()将所有图像无差别地添加到队列中。

参考

拼接。图像拼接 - OpenCV API文档，已访问2014-02-26，<http://docs.opencv.org/modules/stitching/doc/stitching.html>
OpenCV Stitching示例（Stitcher class，Panorama），已访问2014-02-26，<http://feelmare.blogspot.ca/2013/11/opencv-stitching-example-stitcher-class.html>
全景 - OpenCV中的图像拼接，已访问2014-02-26，<http://ramsrigoutham.com/2012/11/22/panorama-image-stitching-in-opencv/>

Answer 1

我使用拼接管道做了一些工作，虽然我不认为自己是该领域的专家，但我确实获得了更好的性能（以及更好的结果）分别调整管道的每个步骤。正如您在图片中看到的，Stitching类只不过是此管道的包装器： An overview to the Stitching pipeline

你可以调整的一些有趣的部分是调整大小的步骤（有一点是更多的分辨率只是意味着更多的计算时间和更多不准确的功能），匹配过程和（尽管这只是一个猜测）给出一个很好的相机参数而不是执行估计。这涉及在进行拼接之前获取相机参数，但这并不是很难。在这里你有一些参考：OpenCV Camera Calibration and 3D Reconstruction。

再说一遍：我不是专家，这只是基于我作为实习生在图书馆做实验的经验！

Answer 2

据我所知，除了给它一个图像列表之外，没有办法向OpenCV引擎提供额外的数据。虽然它自己做得很好。我会查看一些示例代码，并测试每个拼接操作需要多长时间。从我使用4x6,4x8，...，4x20全景重建的实验中，所需的CPU时间似乎随着重叠图像的数量而增加。我想你的情况至少需要一分钟才能在现代机器上进行计算。

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

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39  // the use of this software, even if advised of the possibility of such damage.
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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

Answer 3

考虑在Opencv Stitcher中启用GPU：

bool try_use_gpu = true;
Stitcher myStitcher = Stitcher::createDefault(try_use_gpu); 
Stitcher::Status status = myStitcher.stitch(Imgs, pano);

Answer 4

也许这会有所帮助？ https://software.intel.com/en-us/articles/fast-panorama-stitching

具体是关于成对匹配的部分

罗南

Answer 5

如果您知道图像的相对位置，您似乎可以将问题分解为子问题，并可能通过了解问题的子结构来接近它来减少计算负荷。基本上将图像集分成4个相邻图像的组，处理帧，然后使用相同的想法处理生成的图像，直到您到达全景图。话虽这么说，我最近才开始玩这个opencv工具集。我知道这是一个非常简单的想法，但它可能对某人有用。

OpenCV - 从图像网格拼接图像

5 个答案: