Is it possible to conduct pose estimation by matching features between picture taken from camera and pre-taken environmental photos?

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Hi, Tatragramm, thank you for your confirm. Just as your explanation, my current problem is how to reconstruct a good 3d environment from your environmental photos? Any recommendation? Someone told me that I have to consider the focal length and FOV of the camera when taking the environment photos. Any comment. Thanks,

The problem is either structure from motion (very hard) if you don't have a tracked camera or a reference point. If you do have a tracked camera then it's triangulation easy. A tracked camera is anything you can locate the pose of wherever it is.

If you have one known landmark (say your poster or an aruco marker) then it's SLAM. Simultaneous Localization and Mapping (medium/hard).

I can point you at some good triangulation code. SfM has an OpenCV module, and I have no idea where to find a good SLAM library. The good algorithms for SLAM have changed so much recently.

Thank you, Tatragramm. Is it possible to achieve pose estimation with solvePnP() without SLAM? The scenario is similar to what I explained in my previous post that I set a physical spot as the original of the world coordinate system and build the virtual room a long with photo texture walls accordingly. So, by feature matching camera captured's image with photo textured walls, can I perform pose estimation with solvePnP? Thanks,