TY  - JOUR
T1  - 3-D Motion Estimation of Elastic Body from Monocular Image Sequenc Using MRF with Entropic Constraints
AU - , Yunhua Zhang AU - , Yaming Wang AU - , Wenqing Huang 
JO  - International Journal of Soft Computing
VL  - 1
IS  - 2
SP  - 128
EP  - 132
PY  - 2006
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2006.128.132
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2006.128.132
KW  - 3-D elastic motion
KW  -motion estimation
KW  -MRF
KW  -entropic constraints
KW  -image sequence
AB  - A novel approach to 3-D motion estimation of elastic body from monocular image sequence is
proposed in this paper. First, with the establishment of feature point correspondence between consecutive
image frames, the affine motion model and the central projection model are presented for local elastic motion.
Then, in order to obtain the global motion parameters and overcome the ill-posed 3-D estimation problem, a
framework of Markov Random Field (MRF) with entropic constraints is proposed. By incorporating the motion
prior constraints into the MRF, the motion smoothness feature between local regions is reflected. This converts
the ill-posed problem into a well-posed one and guarantees the robust solution. Experimental results from a
sequence of synthetic image sequence demonstrate the feasibility of the proposed approach.
ER  -