- Author
- Year
- 2011
- host editors
-
L. Chen
C. Nugent
J. Biswas
J. Hoey - Title
- Human activity recognition from wireless sensor network data: benchmark and software
- Book title
- Activity recognition in pervasive intelligent environments
- Pages (from-to)
- 165-186
- Publisher
- Atlantis Press
- ISBN
- 9789078677352
- Series
- Atlantis ambient and pervasive intelligence, 4
- Document type
- Chapter
- Faculty
- Faculty of Science (FNWI)
- Institute
- Informatics Institute (IVI)
- Abstract
-
Although activity recognition is an active area of research no common benchmark for evaluating
the performance of activity recognition methods exists. In this chapter we present the
state of the art probabilistic models used in activity recognition and show their performance
on several real world datasets. Our results can be used as a baseline for comparing the performance
of other pattern recognition methods (both probabilistic and non-probabilistic).
The datasets used in this chapter are made public, together with the source code of the
probabilistic models used. - Language
- English
- Persistent Identifier
- https://hdl.handle.net/11245/1.354045
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