TY - GEN
T1 - Automatic 3D motion synthesis with time-striding hidden Markov model
AU - Wang, Yi
AU - Liu, Zhi-Qiang
AU - Zhou, Li-Zhu
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2006
Y1 - 2006
N2 - In this paper we present a new method, time-striding hidden Markov model (TSHMM), to learn from long-term motion for atomic behaviors and the statistical dependencies among them. TSHMM is a 2-layer hidden Markov model, which approximates a variable-length hidden Markov model by first-order statistical dependencies. An EM algorithm is proposed to learn the TSHMM. © Springer-Verlag Berlin Heidelberg 2006.
AB - In this paper we present a new method, time-striding hidden Markov model (TSHMM), to learn from long-term motion for atomic behaviors and the statistical dependencies among them. TSHMM is a 2-layer hidden Markov model, which approximates a variable-length hidden Markov model by first-order statistical dependencies. An EM algorithm is proposed to learn the TSHMM. © Springer-Verlag Berlin Heidelberg 2006.
UR - http://www.scopus.com/inward/record.url?scp=33745783106&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-33745783106&origin=recordpage
U2 - 10.1007/11739685_58
DO - 10.1007/11739685_58
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 3540335846
SN - 9783540335849
VL - 3930 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 558
EP - 567
BT - Advances in Machine Learning and Cybernetics - 4th International Conference, ICMLC 2005, Revised Selected Papers
PB - Springer Verlag
T2 - International Conference on Machine Learning and Cybernetics, ICMLC 2005
Y2 - 18 August 2005 through 21 August 2005
ER -