How does feature matching on a non-linear transformation work? Would it be done by trying to approximate the non-linear transformation or through some sort of linear matching-stitching process?
motoole2
I'm not sure if I completely follow the question here, but I'll take a stab. Feel free to follow up / clarify your point though.
The process of matching features should ideally be invariant to the transformation itself. For example, if one wanted to match features between two images captured with fisheye lenses, it should still be possible to do so without additional work. Ideally, one would not need to know how the images were warped.
Instead, we could use matched features to help determine the parameters of a non-linear warp (e.g., take multiple images of a fisheye lens to determine how it distorts images; in fact, this is what was discussed in lecture today ). But this process would only be possible if we can successfully match features in a way that's invariant/robust to the warping operation.
soy
Thank you for the clarification! I was thinking of feature matching between an image before and after a non-linear transformation, so a lot of Monday's lecture also answered my question.
How does feature matching on a non-linear transformation work? Would it be done by trying to approximate the non-linear transformation or through some sort of linear matching-stitching process?
I'm not sure if I completely follow the question here, but I'll take a stab. Feel free to follow up / clarify your point though.
The process of matching features should ideally be invariant to the transformation itself. For example, if one wanted to match features between two images captured with fisheye lenses, it should still be possible to do so without additional work. Ideally, one would not need to know how the images were warped.
Instead, we could use matched features to help determine the parameters of a non-linear warp (e.g., take multiple images of a fisheye lens to determine how it distorts images; in fact, this is what was discussed in lecture today ). But this process would only be possible if we can successfully match features in a way that's invariant/robust to the warping operation.
Thank you for the clarification! I was thinking of feature matching between an image before and after a non-linear transformation, so a lot of Monday's lecture also answered my question.