Title
Automating Image Morphing Using Structural Similarity on a Halfway Domain
Abstract
The main challenge in achieving good image morphs is to create a map that aligns corresponding image elements. Our aim is to help automate this often tedious task. We compute the map by optimizing the compatibility of corresponding warped image neighborhoods using an adaptation of structural similarity. The optimization is regularized by a thin-plate spline and may be guided by a few user-drawn points. We parameterize the map over a halfway domain and show that this representation offers many benefits. The map is able to treat the image pair symmetrically, model simple occlusions continuously, span partially overlapping images, and define extrapolated correspondences. Moreover, it enables direct evaluation of the morph in a pixel shader without mesh rasterization. We improve the morphs by optimizing quadratic motion paths and by seamlessly extending content beyond the image boundaries. We parallelize the algorithm on a GPU to achieve a responsive interface and demonstrate challenging morphs obtained with little effort.
Year
DOI
Venue
2014
10.1145/2629494
ACM Trans. Graph.
Keywords
Field
DocType
poisson extension,algorithms,image interpolation,gpu,motion paths,general,warping,correspondences,parameterization
Morphing,Computer vision,Image warping,Parametrization,Structural similarity,Artificial intelligence,Image scaling,Mathematics
Journal
Volume
Issue
ISSN
33
5
0730-0301
Citations 
PageRank 
References 
23
1.04
28
Authors
6
Name
Order
Citations
PageRank
Jing Liao118225.81
Rodolfo S. Lima2593.81
Diego Nehab374342.58
Hugues Hoppe49563754.57
Pedro V. Sander5111163.92
Jinhui Yu611216.83