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Authors: Tatsuya Kiyohara ; Ryohei Orihara ; Yuichi Sei ; Yasuyuki Tahara and Akihiko Ohsuga

Affiliation: University of Electro-Communications, Japan

Keyword(s): Activity Recognition, Accelerometer, Time Series Data Mining, Sensor Data Mining, Acceleration Sensor, Dynamic Time Warping(DTW), DTW-D.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: Dogs are one of the most popular pets in the world, and more than 10 million dogs are bred annually in Japan now (JPFA, 2013). Recently, primitive commercial services have been started that record dogs’ activities and report them to their owners. Although it is expected that an owner would like to know the dog’s activity in greater detail, a method proposed in a previous study has failed to recognize some of the key actions. The demand for their identification is highlighted in responses to our questionnaire. In this paper, we show a method to recognize the actions of the dog by attaching only one off-the-shelf acceleration sensor to the neck of the dog. We apply DTW-D which is the state-of-the-art time series data search technique for activity recognition. Application of DTW-D to activity recognition of an animal is unprecedented according to our knowledge, and thus is the main contribution of this study. As a result, we were able to recognize ten different activities with 65.8% cla ssification F-measure. (More)

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Paper citation in several formats:
Kiyohara, T.; Orihara, R.; Sei, Y.; Tahara, Y. and Ohsuga, A. (2015). Activity Recognition for Dogs Using Off-the-Shelf Accelerometer. In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-074-1; ISSN 2184-433X, SciTePress, pages 100-110. DOI: 10.5220/0005212001000110

@conference{icaart15,
author={Tatsuya Kiyohara. and Ryohei Orihara. and Yuichi Sei. and Yasuyuki Tahara. and Akihiko Ohsuga.},
title={Activity Recognition for Dogs Using Off-the-Shelf Accelerometer},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2015},
pages={100-110},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005212001000110},
isbn={978-989-758-074-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Activity Recognition for Dogs Using Off-the-Shelf Accelerometer
SN - 978-989-758-074-1
IS - 2184-433X
AU - Kiyohara, T.
AU - Orihara, R.
AU - Sei, Y.
AU - Tahara, Y.
AU - Ohsuga, A.
PY - 2015
SP - 100
EP - 110
DO - 10.5220/0005212001000110
PB - SciTePress