Image & MOCAP Synchronized Dataset (v. 1.0)

This data in part was used as a ground truth for the quantitative evaluation of tracking using the loose-limbed body model presented at CVPR 2004. The data is available for research purposes only, please see the full copyright notice bellow. For non-comercial uses, please email me ( ls@cs.brown.edu ) for the login and password.

Download data and example code (password protected)

Image data only [zip]

Image data and ground truth [zip]
Download required library [Camera Calibration Toolbox for Matlab]

Related Papers:

Tracking loose-limbed people,
Sigal, L., Bhatia, S., Roth, S., Black, M. J., Isard, M.,
IEEE Conf. on Computer Vision and Pattern Recognition, vol. I, pp. 421-428, June 2004.
[postscript], [pdf]

Gibbs likelihoods for Bayesian tracking,
Roth, S., Sigal, L., Black, M. J.,
IEEE Conf. on Computer Vision and Pattern Recognition, vol. I, pp. 886-893, June 2004.
[postscript], [pdf]

3D human limb detection using space carving and multi-view eigen models,
Bhatia, S., Sigal, L., Isard, M., Black, M. J.,
IEEE Workshop on Articulated and Nonrigid Motion, CDROM Proceedings, Washington DC, June 2004.
[postscript], [pdf]

Attractive people: Assembling loose-limbed models using non-parametric belief propagation,
Sigal, L., Isard, M. I., Sigelman, B. H., Black, M. J.,
to appear: Advances in Neural Information Processing Systems 16, NIPS 2003.
[postscript], [pdf]

Copyright 2004, Leonid Sigal
All Rights Reserved Permission to use, copy, modify, and distribute this software and its documentation for any non-commercial purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation, and that the name of the author not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

Pampas / Non-parametric Belief Propagation Toolbox for Matlab (v. 0.1)

This toolbox is an implementation of "Pampas: Real-Valued Graphical Models for Computer Vision" published by M. Isard. This is the base implementation of the Non-parametric Belief Propagation (NBP) algorithm, that also contains simple example code and short documentation on how this implementation can be extended for other applications. The data is available for research purposes only, please see the full copyright notice bellow. For non-commercial uses, please email me ( ls@cs.brown.edu ) for the login and password. This toolbox in an on-going effort, for bug reports and suggestions please contact me.

Pampas / Non-parametric Belief Propagation Toolbox (password protected)

Source code for Matlab (v. 0.1) [zip]

Documentation [html]

Introduction [pdf] (comming soon)
Download required library [Kernel Density Estimation Toolbox for Matlab] (currently included in distribution).

Update Log:

Date	Description
5/11/2005	Toolbox is released for general public use (v. 0.1)

Related Papers:

Attractive people: Assembling loose-limbed models using non-parametric belief propagation,
Sigal, L., Isard, M. I., Sigelman, B. H., Black, M. J.,
to appear: Advances in Neural Information Processing Systems 16, NIPS 2003.
[postscript], [pdf]

Copyright 2005, Leonid Sigal
All Rights Reserved Permission to use, copy, modify, and distribute this software and its documentation for any non-commercial purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation, and that the name of the author not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.