Flow-Guided Warping for Image-Based Shape Manipulation

Romain Vergne 1, * Pascal Barla 2 Georges-Pierre Bonneau 1 Roland Fleming 3
* Corresponding author
1 MAVERICK - Models and Algorithms for Visualization and Rendering
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
2 MANAO - Melting the frontiers between Light, Shape and Matter
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, LP2N - Laboratoire Photonique, Numérique et Nanosciences
Abstract : We present an interactive method that manipulates perceived object shape from a single input color image thanks to a warping technique implemented on the GPU. The key idea is to give the illusion of shape sharpening or rounding by exaggerating orientation patterns in the image that are strongly correlated to surface curvature. We build on a growing literature in both human and computer vision showing the importance of orientation patterns in the communication of shape, which we complement with mathematical relationships and a statistical image analysis revealing that structure tensors are indeed strongly correlated to surface shape features. We then rely on these correlations to introduce a flow-guided image warping algorithm, which in effect exaggerates orientation patterns involved in shape perception. We evaluate our technique by 1) comparing it to ground truth shape deformations, and 2) performing two perceptual experiments to assess its effects. Our algorithm produces convincing shape manipulation results on synthetic images and photographs, for various materials and lighting environments. A simplified demo is provided as an IOS app: see http://bonneau.meylan.free.fr/ShwarpIt/ShwarpIt.html
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Romain Vergne, Pascal Barla, Georges-Pierre Bonneau, Roland Fleming. Flow-Guided Warping for Image-Based Shape Manipulation. ACM Transactions on Graphics, Association for Computing Machinery, 2016, 34 (4), pp.Article No. 93 ⟨10.1145/2897824.2925937⟩. ⟨hal-01307571⟩

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