A classification method of motion database using hidden Markov model

Ayaka Matsui, Satoshi Nishimura, Seiichiro Katsura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a classification method of a stored motion-data. Robotic technology has made progress, and robots are demanded to cooperate with human. To realize the human and robot exist together, a motion recognition system is needed. In the conventional method, the stored motion-data is classified in advance to search the motion quickly and accurately. However, the task of the classification will be very complex when the stored data is increased. Therefore, the classification system of stored data automatically is required. Since the human motion is time series information and unsteady signal, a hidden Markov Model is used as the probability models. Additionally, this paper shows that Kullback-Leiblaer divergence indicates the similarity index of the stored motion. At this time, the motion is classified according to the acceleration information, which includes the pure force and position information. The validity of the proposed method is confirmed by simulations.

Original languageEnglish
Title of host publicationIEEE International Symposium on Industrial Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2232-2237
Number of pages6
ISBN (Print)9781479923991
DOIs
Publication statusPublished - 2014
Event2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014 - Istanbul, Turkey
Duration: 2014 Jun 12014 Jun 4

Other

Other2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014
CountryTurkey
CityIstanbul
Period14/6/114/6/4

Fingerprint

Hidden Markov models
Robots
Time series
Robotics

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

Cite this

Matsui, A., Nishimura, S., & Katsura, S. (2014). A classification method of motion database using hidden Markov model. In IEEE International Symposium on Industrial Electronics (pp. 2232-2237). [6864965] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIE.2014.6864965

A classification method of motion database using hidden Markov model. / Matsui, Ayaka; Nishimura, Satoshi; Katsura, Seiichiro.

IEEE International Symposium on Industrial Electronics. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2232-2237 6864965.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Matsui, A, Nishimura, S & Katsura, S 2014, A classification method of motion database using hidden Markov model. in IEEE International Symposium on Industrial Electronics., 6864965, Institute of Electrical and Electronics Engineers Inc., pp. 2232-2237, 2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014, Istanbul, Turkey, 14/6/1. https://doi.org/10.1109/ISIE.2014.6864965
Matsui A, Nishimura S, Katsura S. A classification method of motion database using hidden Markov model. In IEEE International Symposium on Industrial Electronics. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2232-2237. 6864965 https://doi.org/10.1109/ISIE.2014.6864965
Matsui, Ayaka ; Nishimura, Satoshi ; Katsura, Seiichiro. / A classification method of motion database using hidden Markov model. IEEE International Symposium on Industrial Electronics. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 2232-2237
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