Plan Synthesis for Probabilistic Activity Recognition

Frank Krüger, Kristina Yordanova, Albert Hein, Thomas Kirste

2013

Abstract

We analyze the applicability of model-based approaches to the task of inferring activities in smart environments. We introduce a symbolic approach to representing human behavior that enables the use of prior knowledge on the causality of human action and outline its probabilistic semantics. Based on an experimental analysis of a real world scenario from the smart meeting room domain, we show that such a symbolic approach allows to build reusable behavior models that compete with data-driven models at the performance level and that are able to track human behavior across a wide range of scenarios.

References

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Paper Citation


in Harvard Style

Krüger F., Yordanova K., Hein A. and Kirste T. (2013). Plan Synthesis for Probabilistic Activity Recognition . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8565-39-6, pages 283-288. DOI: 10.5220/0004256002830288


in Bibtex Style

@conference{icaart13,
author={Frank Krüger and Kristina Yordanova and Albert Hein and Thomas Kirste},
title={Plan Synthesis for Probabilistic Activity Recognition},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2013},
pages={283-288},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004256002830288},
isbn={978-989-8565-39-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Plan Synthesis for Probabilistic Activity Recognition
SN - 978-989-8565-39-6
AU - Krüger F.
AU - Yordanova K.
AU - Hein A.
AU - Kirste T.
PY - 2013
SP - 283
EP - 288
DO - 10.5220/0004256002830288