The experiment from Hernan Badino was redone. You can see it there...
<https://www.youtube.com/watch?v=fqWdSfN9FiA> Source
The main interest is that video is looping, and the result is almost:
<https://www.youtube.com/watch?v=0ZPJmnBh03M> Reworked
Well, Hernan Badino is moving his head when he is walking, so the reconstructed trajectory is not perfectly looping at the end. But
we can reconstruct the movement almost perfectly. We use OpenCV
for image processing, and POV-Ray for 3D representation. We have
to determine projective dominant motion in the video with a
reference image, and change it when correlation drops below 80%.
We have a 3D inertial model of motion, that's why POV-Ray helps =)
The principle of dominant 2D motion appeared at INRIA, it is here:
<https://www.irisa.fr/vista/Themes/Logiciel/Motion-2D/Motion-2D.html>
In our case, the dominant motion estimated from the approximation of optical-flow (DIS - Dense Inverse Search OpenCV) is 3D and projective.
Francois LE COAT writes:
The experiment from Hernan Badino was redone. You can see it there...
<https://www.youtube.com/watch?v=fqWdSfN9FiA> Source
The main interest is that video is looping, and the result is almost:
<https://www.youtube.com/watch?v=0ZPJmnBh03M> Reworked
Well, Hernan Badino is moving his head when he is walking, so the
reconstructed trajectory is not perfectly looping at the end. But
we can reconstruct the movement almost perfectly. We use OpenCV
for image processing, and POV-Ray for 3D representation. We have
to determine projective dominant motion in the video with a
reference image, and change it when correlation drops below 80%.
We have a 3D inertial model of motion, that's why POV-Ray helps =)
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