Title
Learning skeletons for shape and pose
Abstract
In this paper a method for estimating a rigid skeleton, including skinning weights, skeleton connectivity, and joint positions, given a sparse set of example poses is presented. In contrast to other methods, we are able to simultaneously take examples of different subjects into account, which improves the robustness of the estimation. It is additionally possible to generate a skeleton that primarily describes variations in body shape instead of pose. The shape skeleton can then be combined with a regular pose varying skeleton. That way pose and body shape can be controlled simultaneously but separately. As this skeleton is technically still just a skinned rigid skeleton, compatibility with major modelling packages and game engines is retained. We further present an approach for synthesizing a suitable bind shape that additionally improves the accuracy of the generated model.
Year
DOI
Venue
2010
10.1145/1730804.1730809
SI3D
Field
DocType
Citations 
Computer vision,Skinning,Computer science,Robustness (computer science),Artificial intelligence,Skeleton (computer programming)
Conference
13
PageRank 
References 
Authors
0.68
18
4
Name
Order
Citations
PageRank
Nils Hasler127211.28
Thorsten Thormählen2130.68
Bodo Rosenhahn31733137.77
Hans-Peter Seidel412532801.49