4 ms·

This same algorithm could be applied in three dimensions (X, Y, time) such that the seam connects along adjacent pixels through time as well as the Y axis. The

This same algorithm could be applied in three dimensions (X, Y, time) such that the seam connects along adjacent pixels through time as well as the Y axis. The seam here would be a 2D plane, rather than a 1D line as it is for a single image. If you visualize a video as a stack of frames, then the seam would cut through the stack, like cutting a cake with a knife, following the minimum-energy path through the stack. You'd do this by modifying the recurrence relation to add a term for the energy of pixels in the previous frame as well as the previous line in the current frame.

gamegoblin 7y ago
I don't think it's necessarily so simple, and I think the multi-frame case blows up the complexity of the algorithm. In the single frame case, each pixel is a 0 dimensional point, and for each pixel, you evaluate the 3 adjacent pixels in the row above. Then to find the seam you just pick the lowest energy pixel at the edge of the frame and follow the thread up. So the total runtime of this algorithm is O(pixels). In the multi-frame case, if you want the video to be totally smooth, you have to think higher-dimensionally. In the multi frame case, each seam is a 1 dimensional list of pixels, and for each seam, you evaluate the $HUGE_NUMBER of adjacent seams in the previous frame. That is, the 2D case's runtime is proportional to the image height times the number of adjacent pixels, which is a small constant (3). In the 3D case, the runtime is proportional to the number of frame times the number of adjacent seams, which is massive. I can imagine some heuristic optimizations that would allow you to guide your search, though. For instance, you could significantly downsample the video in both pixels and framerate and solve that, and then use that low-resolution solution to constrain and prune an approximate high-resolution search.
dTal 7y ago
I think this is the correct way to conceptualize generalizing this algorithm to moving video. I also think it's a fundamentally bad approach to resizing video. The problem is that humans watching the video will build a 3D mental model of the scene; any transform that modifies multiple frames must do so in such a way as to maintain global spatial consistency, or it will look odd. Seam carving is too primitive to do this. You will have shots where (for instance) someone is walking obliquely away from a building towards the camera, and yet making no headway because the algorithm is carving away the (low energy, yet perceptually indispensible) pixels that seperate them - the result will be that they appear to be walking in place (and growing).
- Robin_Message 7y ago
  I have to say, that sounds like it might be an awesome effect!
  - dTal 7y ago
    Apparently seam carving is already used to produce surreal memes: https://imgur.com/gallery/NpeguXu https://imgur.com/gallery/NpeguXu
ambicapter 7y ago
That would get pretty funky when the scene changes.

gamegoblin 7y ago

I don't think it's necessarily so simple, and I think the multi-frame case blows up the complexity of the algorithm. In the single frame case, each pixel is a 0 dimensional point, and for each pixel, you evaluate the 3 adjacent pixels in the row above. Then to find the seam you just pick the lowest energy pixel at the edge of the frame and follow the thread up. So the total runtime of this algorithm is O(pixels). In the multi-frame case, if you want the video to be totally smooth, you have to think higher-dimensionally. In the multi frame case, each seam is a 1 dimensional list of pixels, and for each seam, you evaluate the $HUGE_NUMBER of adjacent seams in the previous frame. That is, the 2D case's runtime is proportional to the image height times the number of adjacent pixels, which is a small constant (3). In the 3D case, the runtime is proportional to the number of frame times the number of adjacent seams, which is massive. I can imagine some heuristic optimizations that would allow you to guide your search, though. For instance, you could significantly downsample the video in both pixels and framerate and solve that, and then use that low-resolution solution to constrain and prune an approximate high-resolution search.

dTal 7y ago

I think this is the correct way to conceptualize generalizing this algorithm to moving video. I also think it's a fundamentally bad approach to resizing video. The problem is that humans watching the video will build a 3D mental model of the scene; any transform that modifies multiple frames must do so in such a way as to maintain global spatial consistency, or it will look odd. Seam carving is too primitive to do this. You will have shots where (for instance) someone is walking obliquely away from a building towards the camera, and yet making no headway because the algorithm is carving away the (low energy, yet perceptually indispensible) pixels that seperate them - the result will be that they appear to be walking in place (and growing).

Robin_Message 7y ago
I have to say, that sounds like it might be an awesome effect!
- dTal 7y ago
  Apparently seam carving is already used to produce surreal memes: https://imgur.com/gallery/NpeguXu https://imgur.com/gallery/NpeguXu

ambicapter 7y ago

That would get pretty funky when the scene changes.