Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University

Digital Library

Javascript is currently disabled for your browser. For an optimal search experience, please enable javascript.

Advanced Search

Basic Search

Content Type

Topics

Publication Date

Poster

Foundations for Summarizing and Learning Latent Structure in Video

  • October 2017
  • By Kevin A. Pitstick506730
  • Poster on use of machine learning to develop automated and semantically meaningful video summarization
  • Publisher: Software Engineering Institute
  • Abstract

    Video data from a variety of DoD platforms is proliferating in the modern battlespace, and expanded dissemination of this video makes it widely available. However, the detection of artifacts of interest in streaming surveillance video is a manually intensive process. As the volume of video data continues to increase, automated video summarization that highlights artifacts of interest is needed. In this work, we are developing automated and semantically meaningful video summarization and sense making to improve situational awareness, reduce the amount of manual processing necessary, and increase the volume of video data that can be analyzed in near real-time.

  • Download