This is göynük canyon, turkey.
For skew I have some ideas in todo list. It is quite easy to match frames to each other using 2 sets of parameters instead of 1 (same as deshaker).
Then it is quite easy to try full compensation matching all frames to single reference frame, this is suitable for shots without motion. This should certainly work, but I am not sure RS is an issue at all with such shots.
The trouble is to build a path when camera moves. I certainly cannot just accumulate differences stacking one frame after another: this works for no-skew mode but with skew included the growing error tears frame apart.
I tried deshaker approach without success (either I did it wrong or did not understand the result), also tried filtered average as immediate reference (same here).
Another idea is to collect frames with lowest skew and use them as references.
First I need better motion data. For this I started to make analyzer
Second problem is to understand what happens. This is hard with real footage. I dont see something simple like skewed pillar, instead the shot just looks "jelly" but I cant tell for each frame where it is wrong.
To some extent I train the math on synthetic RS-skewed shots. This way I can have perfect result to compare with. But I need to go deeper and prepare realistic synthetic shot with motion and shaking similar to reality, and this is damn long task to prepare
For wobble I have no ideas. I suppose it requires different level of enginery (structure from motion etc).
I chose as milestone some piece of footage which has really bad shake but still no wobble.
Btw maybe by the time I finish that, they come up with practical global shutter sensor?