Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security

Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security

Hans W. Guesgen, Stephen Marsland
Indexed In: SCOPUS View 1 More Indices
Release Date: March, 2013|Copyright: © 2013 |Pages: 378
DOI: 10.4018/978-1-4666-3682-8
ISBN13: 9781466636828|ISBN10: 1466636823|EISBN13: 9781466636835
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Description & Coverage
Description:

Recently, the ICT field has seen a shift from machine-centered focuses to human and user knowledge-based approaches. However, as priorities shift, questions arise on how to detect and monitor users’ behavior.

Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security takes an insightful look into the applications and dependability of behavior detection. In addition, this comprehensive publication looks into the social, ethical, and legal implications of these areas.   Researchers and practitioners interested in the computational aspects of behavior monitoring as well as the ethical and legal implications will find this reference source beneficial.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Behavior Interpretation
  • Behavior Management
  • Human Aspects of Technology
  • IT Research and Theory
  • IT Security and Ethics
  • Web Technologies
Reviews & Statements

In this reference intended for researchers and practitioners, editors Guesgen and Marsland (Massey U., New Zealand) and 36 contributors examine applications and reliability of human behavior recognition technologies as well as social, legal, and ethical considerations. A sampling of specific topics addressed includes: a logic-based approach to activity recognition, ontology-based real-time behavior interpretation, tracking systems for multiple smart home residents, sensors for smart homes, monitoring social life and interactions, from streams of observation to knowledge-level productive predictions, and motion and location-based online human daily activity recognition.

– Annotation ©2013 Book News Inc. Portland, OR
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Editor/Author Biographies
Hans Guesgen is a Professor of Computer Science in the School of Engineering and Advanced Technology (SEAT) at Massey University in New Zealand. His research interests include ambient intelligence, smart environments, knowledge representation, constraint satisfaction, spatio-temporal and qualitative reasoning, with more than 100 refereed papers in these areas. He holds a doctorate in computer science of the University of Kaiserslautern, and a higher doctorate (Habilitation) in computer science of the University of Hamburg, Germany. Hans is a senior member of the Association for the Advancement of Artificial Intelligence (AAAI) and an honorary research associate of the Computer Science Department of the University of Auckland, New Zealand.
Stephen Marsland is Professor of Scientific Computing in the School of Engineering and Advanced Technology (SEAT) at Massey University in New Zealand. He has a degree in mathematics from Oxford University and a PhD from Manchester University. He arrived at Massey in 2004 following postdoc positions in the US and Europe. Stephen's research interests lie in the areas of Euler equations on diffeomorphism groups, machine learning and behaviour recognition, and complexity. He is currently supported by the RSNZ Marsden Fund.
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