Title
Content-based multimedia analytics: US and NATO research
Author
Bowman, E.K.
Burghouts, G.
Overlier, L.
Kase, S.E.
Zimmerman, R.J.
Oggero, S.
Contributor
Llinas, J. (editor)
Hanratty, T.P. (editor)
Publication year
2018
Abstract
The US and nations of the NATO Alliance are increasingly threatened by the global spread of terrorism, humanitarian crises/disaster response, and public health emergencies. These threats are influenced by the unprecedented rise of information sharing technologies and practices, where mobile access to social networking sites is ubiquitous. In this new information environment, agile data algorithms, machine learning software, and threat alert mechanisms must be developed to automatically create alerts and drive quick response. US science and technology investments in Artificial Intelligence and Machine Learning (AI/ML) and Human Agent Teaming (HAT) are increasingly focused on developing capabilities toward that end. A critical foundation of these technologies is the awareness of the underlying context to accurately interpret machine-processed warnings and recommendations. In this sense, context can be a dynamic characteristic of the operating environment and demands a multi-analytic approach. In this paper, we describe US doctrine that formulates capability requirements for operations in the information environment. We then describe a promising social computing approach that brings together information retrieval strategies using multimedia sources that include text, video, and imagery. Social computing is used in this case to increase awareness of societal dynamics at various scales that influence and impact military operations in both the physical and information domains. Our focus, content based information retrieval and multimedia analytics, involves the exploitation of multiple data sources to deliver timely and accurate synopses of data that can be combined with human intuition and understanding to develop a comprehensive worldview. © 2018 SPIE. Downloading of the abstract is permitted for personal use only. The Society of Photo-Optical Instrumentation Engineers (SPIE)
Subject
Information environment
multimedia analytics
Text and video analytics
Artificial intelligence
Digital storage
Information retrieval
Learning systems
Military operations
Content-based information retrieval
Content-based multimedia
Machine learning software
Multimedia analytics
Social computing
Social networking sites
Video analytics
Social sciences computing
To reference this document use:
http://resolver.tudelft.nl/uuid:945be53e-4c81-4321-8067-3032391ec522
TNO identifier
820511
Publisher
SPIE
ISBN
9781510618176
ISSN
0277-786X
Source
Next-Generation Analyst VI 2018. 16 April 2018 through 17 April 2018, 10653
Series
Proceedings of SPIE - The International Society for Optical Engineering
Article number
106530H
Document type
conference paper