Context-Enhanced Information Fusion: Boosting Real-World Performance with Domain Knowledge

ISBN-13: 9783319804644 / Angielski / Miękka / 2018 / 703 str.

Lauro Snidaro; Jesus Garcia; James Llinas

Spis treści

Part I: Foundations

Context and Fusion: Definitions, Terminology
James Llinas, Lauro Snidaro, Jesús García, and Erik Blasch

Part II: Concepts of Context for Fusion

Formalization of “Context” for Information Fusion
Galina L. Rogova and Alan Steinberg

Context as an Uncertain Source
James Llinas, Anne-Laure Jousselme, and Geoff Gross

Contextual Tracking Approaches in Information Fusion
Erik Blasch, Chun Yang, Jesús García, Lauro Snidaro, and James Llinas

Context Assumptions for Threat Assessment Systems
Steven A. Israel and Erik P. Blasch

Context-Aware Knowledge Fusion for Decision Support
Alexander Smirnov, Tatiana Levashova, and Nikolay Shilov

Part III: Systems Philosophy of Contextual Fusion

System-Level Use of Contextual Information
Alan Steinberg and Galina Rogova

Architectural Aspects for Context Exploitation in Information Fusion
Jesús García, Lauro Snidaro, and James Llinas

Middleware for Exchange and validation of context data and information
Jurgo-Soren Preden, James Llinas and Leo Motus

Modeling User Behaviors to Enable Context-Aware Proactive Decision Support
Benjamin Newsom, Ranjeev Mittu, Mark A. Livingston, Stephen Russell, Jonathan W. Decker, Eric Leadbetter, Ira S. Moskowitz, Antonio Gilliam, Ciara Sibley, Joseph Coyne, and Myriam Abramson

Part IV: Mathematical Characterization of Context

Supervising the Fusion Process by Context Analysis for Target Tracking
Vincent Nimier

Context Exploitation for Target Tracking
Giulia Battistello, Michael Mertens, Martin Ulmke, and Wolfgang Koch

Contextual Tracking in Surface Applications: Algorithms and Design Examples
Adam M. Fosbury, John L. Crassidis, and Jemin George

Context Relevance for Text Analysis and Enhancement for Soft Information Fusion
Michael Kandefer and Stuart C. Shapiro

Algorithms for Context Learning and Information Representation for Multi-Sensor Teams
Nurali Virani, Soumalya Sarkar, Ji-Woong Lee, Shashi Phoha, and Asok Ray

Part V: Context in Hard/Soft Fusion

Context for Dynamic and Multi-Level Fusion
Lauro Snidaro and Ingrid Visentini

Multi-Level Fusion of Hard and Soft Information for Intelligence
Joachim Biermann, Jesús García, Ksawery Krenc, Vincent Nimier, Kellyn Rein, and Lauro Snidaro

Context-Based Fusion of Physical and Human Data for Level 5 Information Fusion
Erik Blasch, Riad I. Hammoud, Haibin Ling, Dan Shen, James Nagy, and Genshe Chen

Context Understanding from Query-Based Streaming Video
Alex J. Aved and Erik P. Blasch

Part VI: Applications of Context Approaches to Fusion

The Role of Context in Multiple Sensor Systems for Public Security
Wolfgang Koch

Entity Association Using Context for Wide-Area Motion Imagery Target Tracking
Erik Blasch, Pengpeng Liang, Xinchu Shi, Peiyi Li, and Haibin Ling

Ground Target Tracking Applications: Design Examples for Military and Civil Domains
Jesús García, Tarunraj Singh, and Dirk Tenne

Context-Based Situation Recognition in Computer Vision Systems
J. Gómez-Romero, Jesús García, M.A. Patricio, M.A. Serrano, and J.M. Molina

Data Fusion Enhanced with Context Information for Road Safety Application
Fernando García, Aurelio Ponz, David Martín, Arturo de la Escalera, and José María Armingol

Context in Robotics and Information Fusion
Domenico D. Bloisi, Daniele Nardi, Francesco Riccio, and Francesco Trapani

O autorze

Dr. Lauro Snidaro is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Udine, Italy. Dr. Jesús García is an Associate Professor in the Computer Science and Engineering Department at the Carlos III University of Madrid, Spain. Dr. James Llinas is an Emeritus Professor in the Department of Industrial and Systems Engineering, and in the Department of Electrical Engineering, at the State University of New York at Buffalo, NY, USA. Dr. Erik Blasch is a Principal Scientist at the Air Force Research Laboratory Information Directorate (AFRL/RIEA) in Rome, NY, USA. The editors and contributors have all been leading experts within the international society of information fusion (ISIF).

Blurb

This interdisciplinary text/reference reviews the fundamental theory and latest methods for including contextual information in fusion process design and implementation. Chapters are contributed by the foremost international experts, spanning numerous developments and applications. The book highlights high- and low-level information fusion problems, performance evaluation under highly demanding conditions, and design principles. A particular focus is placed on holistic approaches that integrate research from different communities, emphasizing the benefit of combining different techniques to overcome the limitations of a single perspective or approach.

 

Topics and features:

 

·         Introduces the essential terminology and core elements in information fusion and context, conveyed with the support of the JDL/DFIG data fusion model

·         Presents key themes for context-enhanced information fusion, including topics derived from target tracking, decision support and threat assessment

·         Discusses design issues in developing context-aware fusion systems, proposing several architectures optimized for context access and discovery

·         Provides mathematical grounds for modeling the contextual influences in representative fusion problems, such as sensor quality assessment, target tracking, robotics, and text analysis

·         Describes the fusion of device-generated (hard) data with human-generated (soft) data

·         Reviews a diverse range of applications where the exploitation of contextual information in the fusion process boosts system performance

 

This authoritative volume will be of great use to researchers, academics, and practitioners pursuing applications where information fusion offers a solution. The broad coverage will appeal to those involved in a variety of disciplines, from machine learning and data mining, to machine vision, decision support systems, and systems engineering.

 

Dr. Lauro Snidaro is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Udine, Italy. Dr. Jesús García is an Associate Professor in the Computer Science and Engineering Department at the Carlos III University of Madrid, Spain. Dr. James Llinas is an Emeritus Professor in the Department of Industrial and Systems Engineering, and in the Department of Electrical Engineering, at the State University of New York at Buffalo, NY, USA. Dr. Erik Blasch is a Principal Scientist at the Air Force Research Laboratory Information Directorate (AFRL/RIEA) in Rome, NY, USA. The editors and contributors have all been leading experts within the international society of information fusion (www.isif.org).