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Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion

Liao, Jing, Bi, Yaxin and Nugent, Chris D. (2011) Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion. In: Knowledge Science, Engineering and Management Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp. 365-376. ISBN 978-3-642-25974-6 [Book section]

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Abstract

Weighting connections between different layers within a lattice structure is an important issue in the process of modeling activity recognition within smart environments. Weights not only play an important role in propagating the relational strengths between layers in the structure, they can be capable of aggregating uncertainty derived from sensors along with the sensor context into the overall process of activity recognition. In this paper we present two weight factor algorithms and experimental evaluation. According to the experimental results, the proposed weight factor methods have a better performance of reasoning the complex and simple activity than other methods.

Item Type:Book section
Keywords:Dempster-Shafer theory of evidence, Activity Recognition, Sensor Fusion
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:25481
Deposited By: Dr Yaxin Bi
Deposited On:20 Jan 2016 12:31
Last Modified:20 Jan 2016 12:31

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