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Given a set of 2d trajectories/paths, where a trajectory is a list of [x,y,time] coordinates, and a new trajectory, how can I recognize which one in the set is most similar to it? The lists may not be of the same length, the time differences not the same.

I've tried using perceptual image hashes of the resulting lines, but this approach seems unreliable.

The measure of similarity should be scale and translation, but not rotation invariant.

Edit: I finally found a library that contains a few algorithms: https://github.com/bguillouet/traj-dist

Given a set of 2d trajectories/paths, where a trajectory is a list of [x,y,time] coordinates, and a new trajectory, how can I recognize which one in the set is most similar to it? The lists may not be of the same length, the time differences not the same.

I've tried using perceptual image hashes of the resulting lines, but this approach seems unreliable.

The measure of similarity should be scale and translation, but not rotation invariant.

I'm trying to recognize 2d gestures that are input with a mouse or touchpad in order to execute commands[0]. For this application, the velocity/acceleration of the movement will not matter.

I found this library that contains a few algorithms: https://github.com/bguillouet/traj-dist

[0] https://github.com/void4/termagic

Given a set of 2d trajectories/paths, where a trajectory is a list of [x,y,time] coordinates, and a new trajectory, how can I recognize which one in the set is "closest" to it? The lists may not be of the same length, the time differences not the same.

I've tried using perceptual image hashes of the resulting lines, but this approach seems unreliable.

The measure of closeness should be scale and translation, but not rotation invariant.

Edit: I finally found a library that contains a few algorithms: https://github.com/bguillouet/traj-dist

Given a set of 2d trajectories/paths, where a trajectory is a list of [x,y,time] coordinates, and a new trajectory, how can I recognize which one in the set is most similar to it? The lists may not be of the same length, the time differences not the same.

I've tried using perceptual image hashes of the resulting lines, but this approach seems unreliable.

The measure of similarity should be scale and translation, but not rotation invariant.

Edit: I finally found a library that contains a few algorithms: https://github.com/bguillouet/traj-dist