Gradient domain editing of deforming mesh sequences

Xu, Weiwei; Zhou, Kun; Yu, Yizhou; Tan, Qifeng; Peng, Qunsheng; Guo, Baining

doi:10.1145/1239451.1239535

Cited by 31 publications

(50 citation statements)

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“…In most interactive modeling applications, the linearization methods in Section 3 are usually enough, and several iterations of the nonlinear optimization methods in Section 4 can be performed to further improve the quality of deformation. When the users want to impose nonlinear constraints, like volume constraint, or the constraints are derived from environment, like mesh animation editing in [43], the nonlinear optimization methods should be chosen. In these cases, the reduced deformable models in [32,35] are preferable due to their interactive performance.…”

Section: Discussionmentioning

confidence: 99%

“…A cascading solver is developed in [42] to achieve interactive performance during deformation. In 2007, Xu et al [43] proposed an alternative linear least-squares deformation solver based on the rigid motion invariant representation in [16]. This method alternatively solves the transformation and vertex positions until convergence.…”

Section: Related Approachesmentioning

confidence: 99%

“…Since the deformation energy function is reduced in each step, this method is guaranteed to converge in theory. This deformation solver is applied to mesh animation editing in [43]. Fig.6 compares the alternating least-squares method with the subspace method in [32].…”

Section: Related Approachesmentioning

confidence: 99%

See 2 more Smart Citations

Gradient Domain Mesh Deformation — A Survey

Zhou

2009

J. Comput. Sci. Technol.

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This survey reviews the recent development of gradient domain mesh deformation method. Different to other deformation methods, the gradient domain deformation method is a surface-based, variational optimization method. It directly encodes the geometric details in differential coordinates, which are also called Laplacian coordinates in literature. By preserving the Laplacian coordinates, the mesh details can be well preserved during deformation. Due to the locality of the Laplacian coordinates, the variational optimization problem can be casted into a sparse linear system. Fast sparse linear solver can be adopted to generate deformation result interactively, or even in real-time. The nonlinear nature of gradient domain mesh deformation leads to the development of two categories of deformation methods: linearization methods and nonlinear optimization methods. Basically, the linearization methods only need to solve the linear least-squares system once. They are fast, easy to understand and control, while the deformation result might be suboptimal. Nonlinear optimization methods can reach optimal solution of deformation energy function by iterative updating. Since the computation of nonlinear methods is expensive, reduced deformable models should be adopted to achieve interactive performance. The nonlinear optimization methods avoid the user burden to input transformation at deformation handles, and they can be extended to incorporate various nonlinear constraints, like volume constraint, skeleton constraint, and so on. We review representative methods and related approaches of each category comparatively and hope to help the user understand the motivation behind the algorithms. Finally, we discuss the relation between physical simulation and gradient domain mesh deformation to reveal why it can achieve physically plausible deformation result.

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Section: Discussionmentioning

confidence: 99%

Section: Related Approachesmentioning

confidence: 99%

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Gradient Domain Mesh Deformation — A Survey

Zhou

2009

J. Comput. Sci. Technol.

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“…In 3D space, several editing frameworks have been developed for deforming mesh sequences. For example, Xu et al [34] cast the edit of mesh sequences into two steps: first adjusting the keyframes to satisfy edit constraints; and then smoothly propagating the deformation of keyframes to the whole sequence.…”

Section: Related Workmentioning

confidence: 99%

Fast as-isometric-as-possible shape interpolation

Zhang

et al. 2015

Computers & Graphics

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“…Because the Laplacian constraint and the rigidity constraint are both nonlinearly dependent on the vertex positions, we adopt an iterative scheme, similar to [9,13,15], to minimize the deformation energy.…”

Section: Introductionmentioning

confidence: 99%

Rigidity Constraints for Large Mesh Deformation

Zhao

Liu

Peng

et al. 2009

J. Comput. Sci. Technol.

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It is a challenging problem of surface-based deformation to avoid apparent volumetric distortions around largely deformed areas. In this paper, we propose a new rigidity constraint for gradient domain mesh deformation to address this problem. Intuitively the proposed constraint can be regarded as several small cubes defined by the mesh vertices through mean value coordinates. The user interactively specifies the cubes in the regions which are prone to volumetric distortions, and the rigidity constraints could make the mesh behave like a solid object during deformation. The experimental results demonstrate that our constraint is intuitive, easy to use and very effective.

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Gradient domain editing of deforming mesh sequences

Cited by 31 publications

References 0 publications

Gradient Domain Mesh Deformation — A Survey

Gradient Domain Mesh Deformation — A Survey

Fast as-isometric-as-possible shape interpolation

Rigidity Constraints for Large Mesh Deformation

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