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Multiple Component Learning 

Papers
P. Dollár, B. Babenko, S. Belongie, P. Perona and Z. Tu
Multiple Component Learning for Object Detection
ECCV 2008, Marseille, France.
[pdf |
bibtex]
B. Babenko, P. Dollár, Z. Tu and S. Belongie
Simultaneous Learning and Alignment: Multi-Instance and Multi-Pose Learning
ECCV 2008: Faces in Real-Life Images, Marseille, France.
[pdf |
bibtex]
Also here is the poster for MCL (ECCV08)
and also for the associated workshop paper (ECCV08-WK),
which should serve the role of an in depth reference to Multiple Instance Learning (MIL).
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Non-Isometric Manifold Learning
Papers
Piotr Dollár, Vincent Rabaud and Serge Belongie
Non-Isometric Manifold Learning: Analysis and an Algorithm
ICML 2007, Corvallis, Oregon.
[pdf |
bibtex]
Piotr Dollár, Vincent Rabaud and Serge Belongie
Learning to Traverse Image Manifolds
NIPS 19, 2006, Vancouver, B.C., Canada.
[pdf |
bibtex]
Longer version of NIPS work [extra 4 page appendix]:
Piotr Dollár, Vincent Rabaud and Serge Belongie Learning to Traverse Image Manifolds
UCSD CS Technical Report #CS2007-0876. Jan. 2007.
[pdf |
bibtex]
The following posters (NIPS06 and
ICML07)
provide a good introduction to our work. Also,
here
are the slides from our ICML talk. And
here
is a video of the talk itself.
Code
If you are interested in obtaining our LSML Matlab code please contact us.
The LSML code requires my basic toolbox, version 2.20 or higher.
Updated as of Mar. 06, 2009, see readme.
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Boundary Learning
The goal is simple: to learn edges and object boundaries from human labeled images while making few
modeling assumptions. Some example training and testing images are given for a number of domains
(click each icon to see some corresponding images, click again to enlarge further).
Mouse boundaries
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Gestalt laws
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Road detection
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Natural images
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Papers
Piotr Dollár, Zhuowen Tu and Serge Belongie
Supervised Learning of Edges and Object Boundaries
CVPR 2006, New York, New York.
[pdf |
bibtex]
Piotr Dollár, Zhuowen Tu, Hai Tao and Serge Belongie
Feature Mining for Image Classification
CVPR 2007, Minneapolis, Minnesota.
[pdf |
bibtex]
Boris Babenko, Piotr Dollár, and Serge Belongie
Task Specific Local Region Matching
ICCV 2007, Rio de Janeiro, Brazil.
[pdf |
bibtex]
Z. Tu, K.L. Narr, P. Dollár, I. Dinov, P.M. Thompson, and A.W. Toga
Brain Anatomical Structure Parsing by Hybrid Discriminative/Generative Models
TMI, 2008.
[pdf |
bibtex]
Here is a poster and some
slides related to this work.
Code
Executables for the BEL edge detection are now
available.
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Behavior Recognition
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This work has close ties to the Smart
Vivarium, an ongoing project to automate the monitoring of animal health and welfare. The specific
problems we are working on include:
- behavior recognition
- tracking
- abnormal activity detection
- large scale deployment
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Papers
Piotr Dollár, Vincent Rabaud, Garrison Cottrell and Serge Belongie
Behavior Recognition via Sparse Spatio-Temporal Features
ICCV VS-PETS 2005, Beijing, China.
[pdf |
bibtex]
Serge Belongie, Kristin Branson, Piotr Dollár, and Vincent Rabaud
Monitoring Animal Behavior in the Smart Vivarium
Measuring Behavior 2005, Wageningen, The Netherlands.
[pdf |
bibtex]
The following poster
provides a good introduction to our work.
Mouse Behavior & Facial Expression Datasets
The datasets, as described in Dollár et. al 2005, are available for
download as a number of zip files. The video is encoded using the
DivX codex, for help obtaining the codec click here.
Mouse Behavior [7 parts]:
set00 |
set01 |
set02 |
set03 |
set04 |
set05 |
set06
Facial Expressions [4 parts]:
set00 |
set01 |
set02 |
set03
If you end up using the dataset or getting classification results,
and you are willing to share your results, we would be grateful. Also,
please cite the above paper if you report results in a publication.
Code
If you are interested in obtaining our code please
contact us. You can see the documentation here, the code requires my
basic toolbox, version 1.03. I will updated this code to be
compatible with the more recent versions of my toolbox in the near future.
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