Large scale video analytics: On-demand, iterative inquiry for moving image research

Virginia Kuhn, Alan Craig, Kevin Franklin, Michael Simeone, Ritu Arora, Dave Bock, Luigi Marini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Video is exploding as a means of communication and expression, and the resultant archives are massive, disconnected datasets. Thus, scholars' ability to research this crucial aspect of contemporary culture is severely hamstrung by limitations in semantic image retrieval, incomplete metadata, and the lack of a precise understanding of the actual content of any given archive. Our aim in the Large Scale Video Analytics (LSVA) project is to address obstacles in both image-retrieval and research that uses extreme-scale archives of video data that employs a human-machine hybrid process for analyzing moving images. We propose an approach that 1) places more interpretive power in the hands of the human user through novel visualizations of video data, and 2) uses a customized on-demand configuration that enables iterative queries.

Original languageEnglish (US)
Title of host publication2012 IEEE 8th International Conference on E-Science, e-Science 2012
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 IEEE 8th International Conference on E-Science, e-Science 2012 - Chicago, IL, United States
Duration: Oct 8 2012Oct 12 2012

Publication series

Name2012 IEEE 8th International Conference on E-Science, e-Science 2012

Other

Other2012 IEEE 8th International Conference on E-Science, e-Science 2012
Country/TerritoryUnited States
CityChicago, IL
Period10/8/1210/12/12

Keywords

  • High performance computing
  • Image edge detection
  • Image retrieval
  • Multimedia databases
  • Software
  • Visualization

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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