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I'm new to openCV and C++. If anyone could help me understand the concept, I would really appreciate it. I have text files of data points which are of floating point precision. Each text file is actually a range image(image obtained from a 3D profilometer). I want to stitch these images by the stitcher in openCV. Now, I would like to feed these text files into openCV, and get the final stitched image also in the floating point precision.

Now, the questions is:

Does the stitcher works with floating points as well? Or it must be in char,... formats?

Thanks in advance!

Mona MK
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  • Would this work in theory? Depth images of same object in different distance dont look very similar... typically some 3D registration (e.g. ICP) is used instead. If you are sure it would work you can use CV_8U precision and let the stitcher compute the transformations. Then compute the final blending yourself for float precision matrices, using those transformations. – Micka Jan 16 '15 at 17:21
  • Thanks Micka, just one thing about your suggestion: after finding the homograph, so far I use planar warper in the stitcher to warp one image to the other. Do you have any idea what this planar warper do exactly, so I can do it manually myself? Normal blending shouldn't be difficult, but replacing this planar warper with it, should I expect missing something in my calculations? There is no clear mathematical explanation about warpers in opencv. – Mona MK Jan 19 '15 at 14:48
  • I guess it is just `cv::warpPerspective` but no guarantee, I never used the openCV stitching pipeline myself. When I was in a Mosaicing project, I had to implement my own real-time stitching pipeline and it was in a time when openCV had no own stitching pipeline... – Micka Jan 19 '15 at 17:27

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I think it is possible, what you need to do is to convert these text files into opencv MAT type images, (in floating point format). see here: openCV Mat.

Then you need to feed these images into opencv stitcher. As in the example in this accepted answer in here Stitching Question

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