Enhancing visual dominance by semantics-preserving image recomposition
We present a semi-automatic photographic recomposition approach that employs a
semantics-preserving warp of the input image to enhance the visual dominance of the main
subjects. Our method uses the tearable image warping method to shift the subjects against
the background (and vice versa), so that their visual dominance is improved, and yet
preserve the desired spatial semantics between the subjects and the background. The
recomposition is guided by a measure of the resulting visual dominance of the main …
semantics-preserving warp of the input image to enhance the visual dominance of the main
subjects. Our method uses the tearable image warping method to shift the subjects against
the background (and vice versa), so that their visual dominance is improved, and yet
preserve the desired spatial semantics between the subjects and the background. The
recomposition is guided by a measure of the resulting visual dominance of the main …
We present a semi-automatic photographic recomposition approach that employs a semantics-preserving warp of the input image to enhance the visual dominance of the main subjects. Our method uses the tearable image warping method to shift the subjects against the background (and vice versa), so that their visual dominance is improved, and yet preserve the desired spatial semantics between the subjects and the background. The recomposition is guided by a measure of the resulting visual dominance of the main subjects. Our user experiment shows the effectiveness of the approach.

Showing the best result for this search. See all results