EigenSkin: real time large deformation character skinning in hardware
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Building efficient, accurate character skins from examples
ACM SIGGRAPH 2003 Papers
Spacetime faces: high resolution capture for modeling and animation
ACM SIGGRAPH 2004 Papers
SCAPE: shape completion and animation of people
ACM SIGGRAPH 2005 Papers
Automatic determination of facial muscle activations from sparse motion capture marker data
ACM SIGGRAPH 2005 Papers
Face transfer with multilinear models
ACM SIGGRAPH 2005 Papers
Stop Staring: Facial Modeling and Animation Done Right
Stop Staring: Facial Modeling and Animation Done Right
Key Point Subspace Acceleration and soft caching
ACM SIGGRAPH 2007 papers
Embedded deformation for shape manipulation
ACM SIGGRAPH 2007 papers
ACM Transactions on Graphics (TOG)
Real-time data driven deformation using kernel canonical correlation analysis
ACM SIGGRAPH 2008 papers
Online dictionary learning for sparse coding
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Face poser: Interactive modeling of 3D facial expressions using facial priors
ACM Transactions on Graphics (TOG)
Sparse reconstruction by separable approximation
IEEE Transactions on Signal Processing
Learning skeletons for shape and pose
Proceedings of the 2010 ACM SIGGRAPH symposium on Interactive 3D Graphics and Games
ACM SIGGRAPH 2010 papers
Stable spaces for real-time clothing
ACM SIGGRAPH 2010 papers
Direct Manipulation Blendshapes
IEEE Computer Graphics and Applications
High-quality passive facial performance capture using anchor frames
ACM SIGGRAPH 2011 papers
Interactive region-based linear 3D face models
ACM SIGGRAPH 2011 papers
Physics-inspired upsampling for cloth simulation in games
ACM SIGGRAPH 2011 papers
Compression and direct manipulation of complex blendshape models
Proceedings of the 2011 SIGGRAPH Asia Conference
Continuous character control with low-dimensional embeddings
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Foundations and Trends® in Machine Learning
Optimization with Sparsity-Inducing Penalties
Foundations and Trends® in Machine Learning
Data-Driven Estimation of Cloth Simulation Models
Computer Graphics Forum
Shading-based dynamic shape refinement from multi-view video under general illumination
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Lightweight binocular facial performance capture under uncontrolled lighting
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Smooth skinning decomposition with rigid bones
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Efficient simulation of example-based materials
EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Near-exhaustive precomputation of secondary cloth effects
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Geodesics in heat: A new approach to computing distance based on heat flow
ACM Transactions on Graphics (TOG)
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We propose a method that extracts sparse and spatially localized deformation modes from an animated mesh sequence. To this end, we propose a new way to extend the theory of sparse matrix decompositions to 3D mesh sequence processing, and further contribute with an automatic way to ensure spatial locality of the decomposition in a new optimization framework. The extracted dimensions often have an intuitive and clear interpretable meaning. Our method optionally accepts user-constraints to guide the process of discovering the underlying latent deformation space. The capabilities of our efficient, versatile, and easy-to-implement method are extensively demonstrated on a variety of data sets and application contexts. We demonstrate its power for user friendly intuitive editing of captured mesh animations, such as faces, full body motion, cloth animations, and muscle deformations. We further show its benefit for statistical geometry processing and biomechanically meaningful animation editing. It is further shown qualitatively and quantitatively that our method outperforms other unsupervised decomposition methods and other animation parameterization approaches in the above use cases.