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Groups > sci.image.processing > #4929
| From | Francois LE COAT <lecoat@atari.org> |
|---|---|
| Newsgroups | sci.image.processing |
| Subject | Re: Optical Inertia |
| Date | 2025-06-18 15:15 +0200 |
| Organization | To protect and to server |
| Message-ID | <102ue4n$3rvec$1@paganini.bofh.team> (permalink) |
| References | (5 earlier) <vhnjv5$3dv75$1@paganini.bofh.team> <vpi39q$3709u$1@paganini.bofh.team> <vsh6ul$1nos2$1@paganini.bofh.team> <1004ogh$2bjmt$1@paganini.bofh.team> <101cd4a$2hveo$1@paganini.bofh.team> |
Hi, Francois LE COAT writes: >>> Until now, drone images came from forests in France. The first images >>> were obtained in the French Vosges. >>> >>> <https://www.youtube.com/watch?v=245yJJrwMQ0> Drone in the forest >>> >>> We are now seeing more and more drones in forests outside of France. >>> The available image sources are diversifying... >> >> Here is a sequence of images of a ballad in the forest. This scene >> is observed by a tracking drone... >> >> <https://www.youtube.com/watch?v=46VWJ6-YqtY> >> >> The camera's movement is estimated in the images using a projective >> dominant motion measurement. The presence of a man in the image sequence >> does not interfere with trajectory estimation, because the character >> occupies a position in the field of vision that is not dominant. The >> dominant motion corresponds to the scrolling of the scenery, that is >> the movement of the forest relative to an observing camera. > > Here is a drone in the forest... > > <https://www.youtube.com/watch?v=h3vhlRBB9tg> Forest > > We also obtain the trajectory in space: <https://skfb.ly/pxGqL> > > It's interesting to note that this trajectory loops. That is to say, > the drone passes over the professional pilot's location, and is in > the same place at the end of the video. > > This proves the quality of the trajectory estimation in space. :-) Here's a long drone flight through a Swedish forest... <https://www.youtube.com/watch?v=ppW5BbDPFHc> Swedish forest We obtain the estimated trajectory in space: <https://skfb.ly/pxZHy> The image matching algorithm doesn't incorporate any prior knowledge about what the camera is observing. This might look like a SLAM (Simultaneous Localization And Mapping) method, which is a sparse method, but what is presented is a global and dense method based on optical-flow measurement (Dense Inverse Search - DIS). This is an algorithm, i.e. a numerical recipe, that does not use artificial neural networks. We obtain a filtered measurement (by a Kalman filter) of physical data. Best regards, -- Dr. François LE COAT CNRS - Paris - France <https://hebergement.universite-paris-saclay.fr/lecoat>
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