TY - GEN
T1 - Adaptive piecewise elastic motion estimation
AU - Di, Huijun
AU - Tao, Linmi
AU - Xu, Guangyou
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - This paper proposes a novel probabilistic graphical model, called MTHMM-P, for partitioning general nonrigid motion into piecewise elastic motion, so as to achieve nonrigid motion estimation without the need of any a priori shape model. To this end, two interrelated sub-problems have to be addressed: partitioning whole motion sequence into several coherent pieces and estimating elastic motion inside each one. The proposed MTHMM-P jointly formulates these two sub-problems. By means of a competition-cooperation partition mechanism and joint inference algorithm, the MTHMM-P can automatically determine the number of pieces as well as adjust the span of each piece by adapting to the input sequence, and at the same time achieve the estimation of piecewise elastic motion. Experiments on the motion of face and body show the capability of the MTHMM-P.
AB - This paper proposes a novel probabilistic graphical model, called MTHMM-P, for partitioning general nonrigid motion into piecewise elastic motion, so as to achieve nonrigid motion estimation without the need of any a priori shape model. To this end, two interrelated sub-problems have to be addressed: partitioning whole motion sequence into several coherent pieces and estimating elastic motion inside each one. The proposed MTHMM-P jointly formulates these two sub-problems. By means of a competition-cooperation partition mechanism and joint inference algorithm, the MTHMM-P can automatically determine the number of pieces as well as adjust the span of each piece by adapting to the input sequence, and at the same time achieve the estimation of piecewise elastic motion. Experiments on the motion of face and body show the capability of the MTHMM-P.
KW - Elastic motion estimation
KW - Probabilistic graphical model
UR - http://www.scopus.com/inward/record.url?scp=84944754393&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-22186-1_21
DO - 10.1007/978-3-319-22186-1_21
M3 - Conference contribution
AN - SCOPUS:84944754393
SN - 9783319221854
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 203
EP - 215
BT - Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings
A2 - Hussain, Abir
A2 - Huang, De-Shuang
A2 - Jo, Kang-Hyun
PB - Springer Verlag
T2 - 11th International Conference on Intelligent Computing, ICIC 2015
Y2 - 20 August 2015 through 23 August 2015
ER -