A framework for modeling the appearance of 3D articulated figures
2000
Conference Paper
ps
This paper describes a framework for constructing a linear subspace model of image appearance for complex articulated 3D figures such as humans and other animals. A commercial motion capture system provides 3D data that is aligned with images of subjects performing various activities. Portions of a limb’s image appearance are seen from multiple views and for multiple subjects. From these partial views, weighted principal component analysis is used to construct a linear subspace representation of the “unwrapped” image appearance of each limb. The linear subspaces provide a generative model of the object appearance that is exploited in a Bayesian particle filtering tracking system. Results of tracking single limbs and walking humans are presented.
Author(s): | Sidenbladh, H. and De la Torre, F. and Black, M. J. |
Book Title: | Int. Conf. on Automatic Face and Gesture Recognition |
Pages: | 368-375 |
Year: | 2000 |
Month: | March |
Department(s): | Perceiving Systems |
Bibtex Type: | Conference Paper (inproceedings) |
Paper Type: | Conference |
Address: | Grenoble, France |
Links: |
pdf
|
BibTex @inproceedings{Black:ICAFGR:2000, title = {A framework for modeling the appearance of {3D} articulated figures}, author = {Sidenbladh, H. and De la Torre, F. and Black, M. J.}, booktitle = {Int. Conf. on Automatic Face and Gesture Recognition}, pages = {368-375}, address = {Grenoble, France}, month = mar, year = {2000}, doi = {}, month_numeric = {3} } |