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Krüger,  Frank ;  Hein,  Albert ;  Yordanova,  Kristina ;  Kirste,  Thomas

Recognising the actions during cooking task (Cooking task dataset)

Rostock :  Universität Rostock ,  2015

The dataset contains the data of acceleration sensors attached to a person during the execution of a kitchen task. It consists of 7 datasets that describe the execution of preparing and having a meal: preparing the ingredients, cooking, serving the meal, having a meal, cleaning the table, and washing the dishes. The aim of the experiment is to investigate the ability of activity recognition approaches to recognise fine-grained user activities based on acceleration data. The results from the dataset can be found in the PlosOne paper "Computational State Space Models for Activity and Intention Recognition. A Feasibility Study" by Krüger et al.

DOI:  10.18453/rosdok_id00000116

http://purl.uni-rostock.de/rosdok/id00000116

Daten:
D2011-KTA-KHY.zip
1.285 MB
MD5: e9bf561353e8158e070d2b98f872d065
Dokumentation:
documentation.pdf
1.188 MB
MD5: 711f373c3cee34a50e523448cc82a307

Lizenz:
Creative Commons Lizenzvertrag
Dieses Werk ist lizenziert unter einer Creative Commons Namensnennung 4.0 International Lizenz.

Jahr der Erstellung:2011
Lokaler Identifikator:D2011-KTA-KHY
Typ:Measurement
Schlagworte:activity recognition
kitchen task assessment
cooking task
Publikationen:

Frank Krüger, Martin Nyolt, Kristina Yordanova, Albert Hein, and Thomas Kirste. Computational state space models for activity and intention recognition. a feasibility study. PLoS ONE, 9(11):e109381, 11 2014.
DOI:10.1371/journal.pone.0109381

Martin Nyolt, Frank Krüger, Kristina Yordanova, Albert Hein, and Thomas Kirste. Marginal filtering in large state spaces. International Journal of Approximate Reasoning, 61:16–32, June 2015.
DOI:10.1016/j.ijar.2015.04.003

Martin Nyolt, Kristina Yordanova, and Thomas Kirste. Checking models for activity recognition. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), pages 497–502, Lisbon, Portugal, January 2015.
DOI:10.5220/0005275204970502

Kristina Yordanova. Methods for Engineering Symbolic Human Behaviour Models for Activity Recognition. PhD thesis, Institute of Computer Science, Rostock, Germany, June 2014.
URN: urn:nbn:de:gbv:28-diss2014-0133-5

Kristina Yordanova and Thomas Kirste. Towards systematic development of symbolic models for activity recognition in intelligent environments. In Proceedings of the The 3rd Workshop on AI Problems and Approaches for Intelligent Environments held at ECAI 2014, Prague, Czech Republic, August 2014.
URL: http://2014.ai4ie.de/ai4ie2014_submission_7.pdf


Dokumenttyp:Datenpublikation
Sprache(n):Englisch
DNB-Sachgruppe:004 Informatik
Fakultät:Fakultät für Informatik und Elektrotechnik

Persistente URL:http://purl.uni-rostock.de/rosdok/id00000116
erstellt am:2015-08-14
zuletzt geändert am:2015-08-14
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.