Scanner is a system for developing applications that efficiently process large video datasets.
To learn more about Scanner, see the documentation at scanner.run, check out the various example applications, or read the SIGGRAPH 2018 Technical Paper: "Scanner: Efficient Video Analysis at Scale".
Documentation
Scanner's documentation is hosted at scanner.run. Here are a few links to get you started:
- Installation
- Getting Started
- Programming Handbook
- API Reference
- SIGGRAPH 2018 Technical Paper
- Scanner Examples
Contributing
If you'd like to contribute to the development of Scanner, you should first build Scanner from source.
Please submit a pull-request rebased against the most recent version of the master branch and we will review your changes to be merged. Thanks for contributing!
Running tests
You can run the full suite of tests by executing make test
in the directory
you used to build Scanner. This will run both the C++ tests and the end-to-end
tests that verify the python API.
About
Scanner is an active research project, part of a collaboration between Stanford and Carnegie Mellon University. Please contact Alex Poms and Will Crichton with questions.
Scanner was developed with the support of the NSF (IIS-1539069), the Intel Corporation (through the Intel Science and Technology Center for Visual Cloud Computing and the NSF/Intel VEC program), and by Google.
Paper citation
Scanner was published at SIGGRAPH 2018 as "Scanner: Efficient Video Analysis at Scale" by Poms, Crichton, Hanrahan, and Fatahalian. If you use Scanner in your research, we'd appreciate it if you cite the paper with the following bibtex:
@article{Poms:2018:Scanner,
author = {Poms, Alex and Crichton, Will and Hanrahan, Pat and Fatahalian, Kayvon},
title = {Scanner: Efficient Video Analysis at Scale},
journal = {ACM Trans. Graph.},
issue_date = {August 2018},
volume = {37},
number = {4},
month = jul,
year = {2018},
issn = {0730-0301},
pages = {138:1--138:13},
articleno = {138},
numpages = {13},
url = {http://doi.acm.org/10.1145/3197517.3201394},
doi = {10.1145/3197517.3201394},
acmid = {3201394},
publisher = {ACM},
address = {New York, NY, USA},
}