Feature detection from illustration of time-series data

Authors:
Tetsuya Takezawa;Toyohide Watanabe
Affiliations:
Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Nagoya, Japan;Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Nagoya, Japan
Venue:
GREC'05 Proceedings of the 6th international conference on Graphics Recognition: ten Years Review and Future Perspectives
Year:
2005

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Abstract

We propose a method for extracting the geometric feature and the comprehensive fluctuation from time-series data and also a method for detecting a reference sequence effectively on the basis of the distance graph. The prevalent methods such as one based on the frequency characteristics do not deal with time-series data in the time dimention. Therefore, our method for extracting the features is temporally sensitive to fluctuations of time-series data. We experimented using the time-series data whose frequency bands were changed variously in order to make clear the availability of the proposal procedures such as smoothing and encoding.