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Regenerative
Morphing CVPR 2010 |
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Eli Shechtman
Alex Rav-Acha Michal Irani Steve Seitz |
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. Regenerative morphing results of a
cloud into a face, and one flower bouquet into another. Both are fully automatic.
In the first example, it is hard to define (even manually)
a set of correspondences between the source images, as required by traditional
morphing. The resulting morphs evolve smoothly from one source image to the
other without loosing their sharp appearance. Note the non-trivial
transitions: facial features (eyes,mouth) deform and merge into close-by
similar cloud patterns, and similar flowers move towards each other while
merging in a seamless way. Abstract We present
a new image morphing approach in which the output sequence is regenerated
from small pieces of the two source (input) images. The approach does not
require manual correspondence, and generates compelling results even when the
images are of very different objects (e.g., a cloud and a face). We pose the
morphing task as an optimization with the objective of achieving
bidirectional similarity of each frame to its neighbors, and also to the
source images. The
advantages of this approach are 1) it can operate fully automatically,
producing effective results for many sequences (but also supports manual
correspondences, when available), 2) ghosting artifacts are minimized, and 3)
different parts of the scene move at different rates, yielding more
interesting (and less robotic) transitions. Demo
video Watch this demo video directly on Vimeo. If for some reason it does not play, you can try this iPhone friendly version. |
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