The Stitched Puppet: A Graphical Model of 3D Human Shape and Pose


Conference Paper


We propose a new 3D model of the human body that is both realistic and part-based. The body is represented by a graphical model in which nodes of the graph correspond to body parts that can independently translate and rotate in 3D as well as deform to capture pose-dependent shape variations. Pairwise potentials define a “stitching cost” for pulling the limbs apart, giving rise to the stitched puppet model (SPM). Unlike existing realistic 3D body models, the distributed representation facilitates inference by allowing the model to more effectively explore the space of poses, much like existing 2D pictorial structures models. We infer pose and body shape using a form of particle-based max-product belief propagation. This gives the SPM the realism of recent 3D body models with the computational advantages of part-based models. We apply the SPM to two challenging problems involving estimating human shape and pose from 3D data. The first is the FAUST mesh alignment challenge (, where ours is the first method to successfully align all 3D meshes. The second involves estimating pose and shape from crude visual hull representations of complex body movements.

Author(s): Silvia Zuffi and Michael J. Black
Book Title: IEEE Conf. on Computer Vision and Pattern Recognition (CVPR 2015)
Pages: 3537--3546
Year: 2015
Month: June

Department(s): Perceiving Systems
Research Project(s): Human Body Models
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

Event Place: Boston, MA, USA

Links: pdf
Extended Abstract


  title = {The Stitched Puppet: A Graphical Model of {3D} Human Shape and Pose},
  author = {Zuffi, Silvia and Black, Michael J.},
  booktitle = { IEEE Conf. on Computer Vision and Pattern Recognition (CVPR 2015)},
  pages = {3537--3546},
  month = jun,
  year = {2015},
  month_numeric = {6}