Accession Number : AD1011094

Title :   Complex Event Processing for Content-Based Text, Image, and Video Retrieval

Descriptive Note : Technical Report,01 Oct 2014,30 Sep 2015

Corporate Author : US Army Research Laboratory Aberdeen Proving Ground United States

Personal Author(s) : Boury-Brisset,Anne-Claire ; Bowman,Elizabeth K ; Burghouts,Gertjan ; Broome,Barbara D ; Duselis,John ; Forrester,Bruce ; Holland,V M ; Howe,Jonathan ; Huis,Jasper van ; Kwantes,Peter ; Madahar,Bhopinder K ; Mlayim,Adem Y ; Rao,Raghuveer M ; Summers-Stay,Douglas

Full Text :

Report Date : 01 Jun 2016

Pagination or Media Count : 42

Abstract : This report summarizes the findings of an exploratory team of the North Atlantic Treaty Organization (NATO) Information Systems Technology panel into Content-Based Analytics (CBA). The team carried out a technical review into the current status of theoretical and practical developments of methods, tools, and techniques supporting joint exploitation of multimedia data sources. In particular, content-based information retrieval and analytics was considered as a means to allow military experts to exploit multiple data sources in a rapid fashion for sensemaking and knowledge generation. Elements included contextual understanding of complex events through computational/human processing techniques, event prediction through the automated extraction of network features, temporal trends, hidden clusters and resource flows, and the use of machine processing for automated translation, parsing, information extraction, and summarization of unstructured and semistructured data. The main conclusions of the study are that important research gaps exist in all the technical areas covered in this report. Though the research areas and developments are being advanced in the military sector and the civil sector, in particular, they remain at low levels of technical maturity for defense and security system applications. It is recommended that this NATO collaborative research effort be expanded to advance those approaches that are most pertinent to our overall aim of enhancing the contextual understanding of complex events through CBA of heterogeneous multimedia streams.

Descriptors :   multimedia , information processing , technology assessment , knowledge management , Text Analytics , artificial intelligence , situational awareness , decision making

Subject Categories : Information Science
      Human Factors Engineering & Man Machine System

Distribution Statement : APPROVED FOR PUBLIC RELEASE