TY - GEN
T1 - A classification method of motion database using hidden Markov model
AU - Matsui, Ayaka
AU - Nishimura, Satoshi
AU - Katsura, Seiichiro
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84907342277&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84907342277&partnerID=8YFLogxK
U2 - 10.1109/ISIE.2014.6864965
DO - 10.1109/ISIE.2014.6864965
M3 - Conference contribution
AN - SCOPUS:84907342277
SN - 9781479923991
T3 - IEEE International Symposium on Industrial Electronics
SP - 2232
EP - 2237
BT - Proceedings - 2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014
Y2 - 1 June 2014 through 4 June 2014
ER -