PhD Research Journals

The registration of 3D surfaces is dealt significantly in the area of machine vision including face recognition. Registration is defined as the estimation of a mapping between coordinate systems that correspond to the same anatomical point (Audette M et. al., 1999).

There are 3 main issues in 3D surface registration:-

(a) choice of transformation,
It concerns about the nature of relationship (transformation) between the two modalities
In face recognition, a rigid-body transformation may be applicable.

Rigid transformation: can be expressed by combining rotation and translation.
Rotation representations are
a) 3 x 3 matrix (rows of matrix define orthogonal axes)
– 9 degree of freedom
b) Euler angles (rotate x, + rotate y + rotate z)
– 3 degree of freedom
c) Axis-angle (axis of rotation + rotation amount)
– 4 degree of freedom
d) Quaternion (4D complex numbers)
– 4 degree of freedom


(b) elaboration of surface representation and similarity criterion,
The type of information extracted from the 3D surfaces, which typically characterised their local and global shape, and organise the gathered information into the a representation of the surface (for efficiency and robustness in the final stage)

(c) matching and global optimisation
Exploiting the information to estimate the transformation which best aligns local primitives globally

In practice, it is good to note that the data (surface information) may contain noise and distortion, and hence this can distort the registration between surfaces.


Reference:

Audette M, Ferrie F and Peters T (1999), An algorithmic overview of surface registrations techniques for medical imaging, Medical Image Analaysis, Oxford University Press