Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Automatic rigging and animation of 3D characters
ACM SIGGRAPH 2007 papers
On Linear Variational Surface Deformation Methods
IEEE Transactions on Visualization and Computer Graphics
Articulated mesh animation from multi-view silhouettes
ACM SIGGRAPH 2008 papers
Performance capture from sparse multi-view video
ACM SIGGRAPH 2008 papers
Geometric skinning with approximate dual quaternion blending
ACM Transactions on Graphics (TOG)
Video-based reconstruction of animatable human characters
ACM SIGGRAPH Asia 2010 papers
Probabilistic deformable surface tracking from multiple videos
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Robust mesh editing using Laplacian coordinates
Graphical Models
Technical Section: Skeleton driven animation based on implicit skinning
Computers and Graphics
3D body pose estimation using an adaptive person model for articulated ICP
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
3D Human model adaptation by frame selection and shape-texture optimization
Computer Vision and Image Understanding
The Vitruvian manifold: Inferring dense correspondences for one-shot human pose estimation
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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We propose a novel formulation to express the attachment of a polygonal surface to a skeleton using purely linear terms. This enables to simultaneously adapt the pose and shape of an articulated model in an efficient way. Our work is motivated by the difficulty to constrain a mesh when adapting it to multi-view silhouette images. However, such an adaption is essential when capturing the detailed temporal evolution of skin and clothing of a human actor without markers. While related work is only able to ensure surface consistency during mesh adaption, our coupled optimization of the skeleton creates structural stability and minimizes the sensibility to occlusions and outliers in input images. We demonstrate the benefits of our approach in an extensive evaluation. The skeleton attachment considerably reduces implausible deformations, especially when the number of input views is limited.