Recognition and classification of human motion based on hidden Markov model for motion database

Yoshihiro Ohnishi, Seiichiro Katsura

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

1 Citation (Scopus)

Abstract

In some countries, many problems according to aging are pointed out. Decrease of worker's physical ability is one of them. The old workers have high techniques, but physical ability is lower than that of young workers. And it becomes difficult to keep high quality. Hence it is thought that a power assist by robot is needed. The method that increases human motion simply is mainstream conventional power assist method. However, to assist accurately it is thought that robot has to recognize human motion and has to assist fitly. Hence, the system that save and reproduce human motion motion database is necessary. Here, to assist accurately, the motion which includes force information is saved to database. In this research, the trajectory information and the force information of human motion is extracted by using bilateral control and it is modeled. To reproduce appropriate motion from database, a search system is needed. For adapting power assist, the search system should be real-time and be able to search at all times. Therefore, in this research, a real-time motion searching method is proposed. The searching method is based on hidden Markov model because human motion has Markov property. Proposed method can search human motion on real-time while human does motion. The viability of proposed method is confirmed by motion search experiment.

Original languageEnglish
Title of host publicationInternational Workshop on Advanced Motion Control, AMC
DOIs
Publication statusPublished - 2012
Event2012 12th IEEE International Workshop on Advanced Motion Control, AMC 2012 - Sarajevo, Bosnia and Herzegovina
Duration: 2012 Mar 252012 Mar 27

Other

Other2012 12th IEEE International Workshop on Advanced Motion Control, AMC 2012
CountryBosnia and Herzegovina
CitySarajevo
Period12/3/2512/3/27

Fingerprint

Hidden Markov models
Markov Model
Motion
Robots
Aging of materials
Trajectories
Real-time
Human
Robot
Experiments
Power Method
Markov Property
Viability
Trajectory

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Modelling and Simulation

Cite this

Recognition and classification of human motion based on hidden Markov model for motion database. / Ohnishi, Yoshihiro; Katsura, Seiichiro.

International Workshop on Advanced Motion Control, AMC. 2012. 6197112.

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

Ohnishi, Y & Katsura, S 2012, Recognition and classification of human motion based on hidden Markov model for motion database. in International Workshop on Advanced Motion Control, AMC., 6197112, 2012 12th IEEE International Workshop on Advanced Motion Control, AMC 2012, Sarajevo, Bosnia and Herzegovina, 12/3/25. https://doi.org/10.1109/AMC.2012.6197112
Ohnishi, Yoshihiro ; Katsura, Seiichiro. / Recognition and classification of human motion based on hidden Markov model for motion database. International Workshop on Advanced Motion Control, AMC. 2012.
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