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Kirste,  Thomas

Detecting high-level team intentions (Three person meeting dataset)

Rostock : Universität Rostock , 2015

https://doi.org/10.18453/rosdok_id00000112

The dataset contains 20 recordings of scripted meetings and an annotation of the performed activities. Three persons (A, B and C) attend the meeting. Each member holds a presentation, and the meeting concludes with a common discussion. This dataset contains the individual team members positions as recorded by an indoor positioning systems.

Datenpublikation Open Access


Lizenz:
Creative Commons Lizenzvertrag (CC-BY)
Dieses Werk ist lizenziert unter einer Creative Commons Namensnennung 4.0 International Lizenz.
Jahr der Erstellung:
2007
Lokaler Identifikator:
D070829-Meeting-MG
Typ:
Measurement
Schlagworte:
team activities
meeting
intention recognition
activity recognition
location
Ubisense
Publikationen:
Nyolt, Martin and Krüger, Frank and Yordanova, Kristina and Hein, Albert and Kirste, Thomas. Marginal filtering in large state spaces. International Journal of Approximate Reasoning, 2015, 61, 16-32.
DOI: https://doi.org/10.1016/j.ijar.2015.04.003
Frank Krüger and Kristina Yordanova and Albert Hein and Thomas Kirste. Plan Synthesis for Probabilistic Activity Recognition. Proceedings of the 5th International Conference on Agents and Artificial Intelligence (ICAART 2013).
DOI: https://doi.org/10.5220/0004256002830288
Kristina Yordanova and Frank Krüger and Thomas Kirste. Context Aware Approach for Activity Recognition Based-on Precondition-Effect Rules. 9th IEEE Workshop on Context Modeling and Reasoning (CoMoRea'12) at the 10th IEEE International Conference on Pervasive Computing and Communication (PerCom'12).
DOI: https://doi.org/10.1109/PerComW.2012.6197586
Krüger, Frank and Yordanova, Kristina and Burghardt, Christoph and Kirste, Thomas. Towards Creating Assistive Software by Employing Human Behavior Models. Journal of Ambient Intelligence and Smart Environments (JAISE), 2012.
DOI: https://doi.org/10.3233/AIS-2012-0148
Kristina Yordanova. Methods for Engineering Symbolic Human Behaviour Models for Activity Recognition. Rostock, 2014.
URN: urn:nbn:de:gbv:28-diss2014-0133-5
Dokumenttyp:
Datenpublikation
Sprache(n):
Englisch
DNB-Sachgruppe:
004 Informatik
Fakultät:
Fakultät für Informatik und Elektrotechnik
Persistente URL:
http://purl.uni-rostock.de/rosdok/id00000112
erstellt am:
2015-08-14
zuletzt geändert am:
2018-06-30
Metadaten-Lizenz:
CC0
Die UB Rostock stellt die Metadaten zu diesem Dokument unter Public Domain und verzichtet damit weltweit auf alle urheberrechtlichen und verwandten Schutzrechte.
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