Video Annotation Tool from Irvine, California

"These are some of the best HITS I've ever done!" — Mechanical Turk worker

vatic is a free, online, interactive video annotation tool for computer vision research that crowdsources work to Amazon's Mechanical Turk. Our tool makes it easy to build massive, affordable video data sets and can be deployed on a cloud. After three years of research, vatic is now used by labs around the world to annotate the next generation of data sets.


Features

News

Code & Download

The latest copy of our code is available for download:

wget http://mit.edu/vondrick/vatic/vatic-install.sh
chmod +x vatic-install.sh
./vatic-install.sh
cd vatic
less README

Please read the README file for proper installation. If you run into any trouble, don't hesitate to contact us.

Data

Samples


Extensions

Other researchers have developed extensions that add additional features to VATIC:

If you use their software in a paper, please cite them appropriately.

Publications

If you use our software or our data sets, please cite:

Carl Vondrick, Donald Patterson, Deva Ramanan. "Efficiently Scaling Up Crowdsourced Video Annotation" International Journal of Computer Vision (IJCV). June 2012. [pdf]

@article {springerlink:10.1007/s11263-012-0564-1,
   author = {Vondrick, Carl and Patterson, Donald and Ramanan, Deva},
   affiliation = {Department of Computer Science, UC Irvine, Irvine, USA},
   title = {Efficiently Scaling up Crowdsourced Video Annotation},
   journal = {International Journal of Computer Vision},
   publisher = {Springer Netherlands},
   issn = {0920-5691},
   keyword = {Computer Science},
   pages = {1-21},
   url = {http://dx.doi.org/10.1007/s11263-012-0564-1},
   note = {10.1007/s11263-012-0564-1},
}

People

Acknowledgements & Funding

We thank Sangmin Oh, Allie Janoch, Sergey Karayev, Kate Saenko, Jenny Yuen, Antonio Torralba, Justin Chen, Will Zou, Baris Evrim Demiroz, Marco Antonio Valenzuela Escarcega, Alper Aydemir, David Owens, Hamed Pirsiavash, our user study participants, and the thousands of annotators for testing our software and offering invaluable insight throughout this study.

Funding for this research was provided by NSF grants 0954083 and 0812428, ONR-MURI Grant N00014-10-1-0933, DARPA Contract No. HR0011-08-C-0135, an NSF Graduate Research Fellowship, support from Intel, and an Amazon AWS grant.

License

Copyright © 2011 Carl Vondrick, Deva Ramanan, and Donald Patterson

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

  1. The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.