A review of deformable surfaces: topology, geometry and deformation

By J. Montagnat, H. Delingette, Nicholas Ayache. Image and Vision Computing, 2001

346 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/60338421137cc3dbafd71f839354abef8ee3df44

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Construction of an abdominal probabilistic atlas and its application in segmentation (2003, methodology): “of the segmentation methods and deformable surface models can be found in [37], [57].”
A Surface Deformation Framework for 3D Shape Recovery (2006, methodology): “Deformation models have widely been used in various modeling problems of 3D computer graphics and vision such as shape recovery, animation, surface editing, tracking and segmentation [1].”
Geodesic Shooting for Computational Anatomy (2006, background): “This second point of view in terms of the conservation of momentum law also sheds new light on a large number of high dimensional evolution based Active Model Methods in Computer Vision, including active snakes and contours [6, 12, 18, 20, 29, 31, 37, 40, 41, 43], active surfaces and deformable mode”
A Bayesian model of shape and appearance for subcortical brain segmentation (2011, neutral): “This is in contrast to the weightings between forces or shape–intensity relations, as used by other approaches (Cootes and Taylor, 2001; Heimann and Meinzer, 2009; Lobregt and Viergever, 1995; Montagnat et al., 2001; Pitiot et al., 2004; Shen et al., 2011), as they typically have a significant effec”
Segmentation of X‐ray computed tomography images of porous materials: A crucial step for characterization and quantitative analysis of pore structures (2009, background): “[Mumford and Shah, 1989; Cohen et al., 1992; McInerney and Terzopoulos, 1996; Caselles et al., 1997; Montagnat and Delingette, 2001 ].”