Context-Enhanced Information Fusion / Advances in Computer Vision and Pattern Recognition (PDF)

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).