Keith Fieldhouse, Matthew J. Leotta, Arslan Basharat, Russell Blue, David Stoup, Chuck Atkins, Linus Sherrill, B. Boeckel, Paul Tunison, Jacob Becker, Matthew Dawkins, Matthew Woehlke, Roderic Collins, M. Turek, A. Hoogs
{"title":"KWIVER: An open source cross-platform video exploitation framework","authors":"Keith Fieldhouse, Matthew J. Leotta, Arslan Basharat, Russell Blue, David Stoup, Chuck Atkins, Linus Sherrill, B. Boeckel, Paul Tunison, Jacob Becker, Matthew Dawkins, Matthew Woehlke, Roderic Collins, M. Turek, A. Hoogs","doi":"10.1109/AIPR.2014.7041910","DOIUrl":null,"url":null,"abstract":"We introduce KWIVER, a cross-platform video exploitation framework that Kitware has begun releasing as open source. Kitware is utilizing a multi-tiered open-source approach to reach as wide an audience as possible. Kitware's government-funded efforts to develop critical defense technology will be released back to the defense community via Forge.mil, a government open source repository. Infrastructure, algorithms, and systems without release restrictions will be provided to the larger video analytics community via kwiver.org and GitHub. Our goal is to provide a video analytics technology baseline for repeatable and reproducible experiments and to serve as a framework for the development of computer vision and machine learning systems. We hope that KWIVER will provide a focal point for collaboration and contributions from groups across the community.","PeriodicalId":210982,"journal":{"name":"2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"281 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2014.7041910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
We introduce KWIVER, a cross-platform video exploitation framework that Kitware has begun releasing as open source. Kitware is utilizing a multi-tiered open-source approach to reach as wide an audience as possible. Kitware's government-funded efforts to develop critical defense technology will be released back to the defense community via Forge.mil, a government open source repository. Infrastructure, algorithms, and systems without release restrictions will be provided to the larger video analytics community via kwiver.org and GitHub. Our goal is to provide a video analytics technology baseline for repeatable and reproducible experiments and to serve as a framework for the development of computer vision and machine learning systems. We hope that KWIVER will provide a focal point for collaboration and contributions from groups across the community.