The authors introduce a technique for 3D surface reconstruction using elastic deformable-models. The model used is an imaginary elastic grid, which is made of membranous, thin-plate-type material. The elastic grid can bent, twisted, compressed, and stretched into any desired 3D shape, which is specified by the shape constraints derived automatically from images of a real 3D object. Shape reconstruction is guided by a set of imaginary springs that enforce the consistency in the position, orientation, and/or curvature measurements of the elastic grid and the desired shape. The dynamics of a surface reconstruction process is regulated by Hamilton's principle or the principle of the least action. Furthermore, a 1D deformable template that borders the elastic grid may be used. This companion boundary template is attracted/repelled by image forces to conform with the silhouette of the imaged object. Implementation results using simple analytic shapes and images of real objects are presented. >
[1]
Yuan-Fang Wang,et al.
Unification scheme for 3D surface reconstruction using physically based models
,
1991,
Int. J. Imaging Syst. Technol..
[2]
J. K. Aggarwal,et al.
3-D structures from 2-D images
,
1988
.
[3]
Yuan-Fang Wang,et al.
Computation of Surface Orientation and Structure of Objects Using Grid Coding
,
1987,
IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4]
Michael Brady,et al.
Computational Approaches to Image Understanding
,
1982,
CSUR.
[5]
G. Hedstrom,et al.
Numerical Solution of Partial Differential Equations
,
1966
.
[6]
Demetri Terzopoulos,et al.
Constraints on Deformable Models: Recovering 3D Shape and Nonrigid Motion
,
1988,
Artif. Intell..