## TR#368: Generalized Image Matching: Statistical Learning of
Physically-Based Deformations

### Chahab Nastar, Baback Moghaddam and Alex Pentland

#### Appeared in: *Fourth European Conference on Computer Vision
*, Cambridge, UK, April 1996.

We describe a novel approach for image matching based on deformable
intensity surfaces. In this approach, the intensity surface of the
image is modeled as a deformable 3D mesh in the (x,y,I(x,y)) space.
Each surface point has 3 degrees of freedom, thus capturing fine
surface changes. A set of representative deformations within a class
of objects (e.g. faces) are statistically learned through a Principal
Components Analysis, thus providing a priori knowledge about
object-specific deformations. We demonstrate the power of the
approach by examples such as image matching and interpolation of
missing data. Moreover this approach dramatically reduces the
computational cost of solving the governing equation for the
physically based system by approximately three orders of magnitude.