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Online context recognition in multisensor systems using Dynamic Time Warping

Ko, Ming Hsiao, West, Geoff, Venkatesh, Svetha and Kumar, Mohan 2005, Online context recognition in multisensor systems using Dynamic Time Warping, in Proceedings of the 2005 intelligent sensors, sensor networks and information processing conference, IEEE, Piscataway, N.J., pp. 283-288, doi: 10.1109/ISSNIP.2005.1595593.

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Title Online context recognition in multisensor systems using Dynamic Time Warping
Author(s) Ko, Ming Hsiao
West, Geoff
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Kumar, Mohan
Conference name Intelligent sensors, sensor networks and information processing conference (2nd : 2005 : Melbourne, Vic.)
Conference location Melbourne, Vic.
Conference dates 5- 8 Dec. 2005
Title of proceedings Proceedings of the 2005 intelligent sensors, sensor networks and information processing conference
Editor(s) Palaniswami, M.
Publication date 2005
Conference series Intelligent Sensors, Sensor Networks and Information Conference
Start page 283
End page 288
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) accelerometers
computer science
embedded computing
hidden Markov models
multimodal sensors
multisensor systems
performance evaluation
pervasive computing
sensor systems
speech recognition
Summary In this paper, we present our system for online context recognition of multimodal sequences acquired from multiple sensors. The system uses Dynamic Time Warping (DTW) to recognize multimodal sequences of different lengths, embedded in continuous data streams. We evaluate the performance of our system on two real world datasets: 1) accelerometer data acquired from performing two hand gestures and 2) NOKIA's benchmark dataset for context recognition. The results from both datasets demonstrate that the system can perform online context recognition efficiently and achieve high recognition accuracy.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 9780780393998
0780393996
Language eng
DOI 10.1109/ISSNIP.2005.1595593
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2005, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044625

Document type: Conference Paper
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.