@inbook{60c99d053fb54a188599486b5f867f8c,
title = "Experimental evaluation of variations in primary features used for accelerometric context recognition",
abstract = "The paper describes initial results in an ongoing project aimed at providing and analyzing standardized representative data sets for typical context recognition tasks. Such data sets can be used to develop user-independent feature sets and recognition algorithms. In addition, we aim to establish standard benchmark data sets that can be used for quantitative comparisons of different recognition methodologies. Benchmark data sets are commonly used in speech and image recognition, but so far none are available for general context recognition tasks. We outline the experimental considerations and procedures used to record the data in a controlled manner, observing strict experimental standards. We then discuss preliminary results obtained with common features on a well-understood scenario with 8 test subjects. The discussion shows that even for a small sample like this variations between subjects are substantial, thus underscoring the need for large representative data sets.",
author = "Heinz, {Ernst A.} and Kunze, {Kai S.} and Stefan Sulistyo and Holger Junker and Paul Lukowicz and Gerhard Tr{\"o}ster",
year = "2003",
doi = "10.1007/978-3-540-39863-9_19",
language = "English",
isbn = "3540204180",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "252--263",
editor = "Emile Aarts and Rene Collier and {van Loenen}, Evert and {de Ruyter}, Boris",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}