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)