http://www.cnr.it/ontology/cnr/individuo/prodotto/ID97199
Contour people: a paremeterized model of 2D articulated human shape (Contributo in atti di convegno)
- Type
- Label
- Contour people: a paremeterized model of 2D articulated human shape (Contributo in atti di convegno) (literal)
- Anno
- 2010-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/CVPR.2010.5540154 (literal)
- Alternative label
O. Freifeld, A. Weiss, S. Zuffi, M. J. Black (2010)
Contour people: a paremeterized model of 2D articulated human shape
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), S. Francisco (USA), 13-18 Giugno 2010
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- O. Freifeld, A. Weiss, S. Zuffi, M. J. Black (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.cs.brown.edu/~zuffi/Site/Welcome_files/freifeldCVPR10.pdf (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Computer Vision and Pattern Recognition (CVPR), 2010 IEEE (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- O. Freifeld, Division of Applied Mathematics, Brown University
A. Weiss, Department of Computer Science, Brown University
S. Zuffi, ITC-CNR and Department of Computer Science, Brown University
M. J. Black, Department of Computer Science, Brown University (literal)
- Titolo
- Contour people: a paremeterized model of 2D articulated human shape (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-1-4244-6984-0 (literal)
- Abstract
- We define a new \"contour person\" model of the human body that has the expressive power of a detailed 3D model and the computational benefits of a simple 2D part-based model. The contour person (CP) model is learned from a 3D SCAPE model of the human body that captures natural shape and pose variations; the projected contours of this model, along with their segmentation into parts forms the training set. The CP model factors deformations of the body into three components: shape variation, viewpoint change and part rotation. This latter model also incorporates a learned non-rigid deformation model. The result is a 2D articulated model that is compact to represent, simple to compute with and more expressive than previous models. We demonstrate the value of such a model in 2D pose es- timation and segmentation. Given an initial pose from a standard pictorial-structures method, we refine the pose and shape using an objective function that segments the scene into foreground and background regions. The result is a parametric, human-specific, image segmentation. (literal)
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