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 2.10 or higher.

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).

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.

Behavior Recognition

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

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.

Selected work that builds on cuboids

Juan Carlos Niebles, Hongcheng Wang and Li Fei-Fei.
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words. BMVC 2006, Edinburgh [author site]

Shu-Fai Wong, Tae-Kyun Kim and Roberto Cipolla,
Learning Motion Categories Using Both Semantic and Structural Information. CVPR, 2007, Minneapolis, Minnesota [author site].