Monday, May 16, 2005
Registration problems
Introduction:
After having almost 2 hrs of discussion with Theodore, who is also during his Phd in the area of face recognition, a few points were brought-up regarding the problems with face recognition. They are the registration and correlation problems.
According to Simon D. (1996), registration problem is concerned with finding a spatial transformation which best aligns (or correlate) two object representations. Correlation is a statistical technique to show whether the two objects are strongly related pairs of variables. Once the registration and correlation problems are solved, mapping can be established. There is a variety of tasks that can be performed using the spatially aligned object representations (aka matching)
The are 3 main matching techniques namely landmark matching, surface matching and intensity matching, which are used in various applications such as medical, science, engineering. These matching techniques helps in registering individual image to form a combined image or insight.
According to Steggmann et. al. (2000), a landmark matching is matching a point on each object to a correspondence point in a population.
Surface matching is a match method based on the structures of interest i.e. the points, lines, curves, surfaces or volumes. In this research, the detailed surface matching techniques will cover the 3D points with 3D structures, matching areas/regions/surfaces (piecewise segment matching of contours).
In Active Appearance Models, intensity matching (aka texture matching) is defined as matching the pixel intensity across the object with the correspondence intensity in another object (Steggmann et. al., 2000).
Discussion:
Here, all the above discussed matching methods will be proposed in the research.
References:
Stefman MB, Fisker R, Ersboll BK, Thodberg HH and Hyldstrup L (2000), Active Appearance Models: Theory and Cases, http://www2.imm.dtu.dk/~aam/main/node34.html (retrieved on the 10 may 2005).
Simon DA (1996), Fast and Accurate Shape-based Registration, PhD Thesis, Carnegie Mellon University, Pittsburgh, US
After having almost 2 hrs of discussion with Theodore, who is also during his Phd in the area of face recognition, a few points were brought-up regarding the problems with face recognition. They are the registration and correlation problems.
According to Simon D. (1996), registration problem is concerned with finding a spatial transformation which best aligns (or correlate) two object representations. Correlation is a statistical technique to show whether the two objects are strongly related pairs of variables. Once the registration and correlation problems are solved, mapping can be established. There is a variety of tasks that can be performed using the spatially aligned object representations (aka matching)
The are 3 main matching techniques namely landmark matching, surface matching and intensity matching, which are used in various applications such as medical, science, engineering. These matching techniques helps in registering individual image to form a combined image or insight.
According to Steggmann et. al. (2000), a landmark matching is matching a point on each object to a correspondence point in a population.
Surface matching is a match method based on the structures of interest i.e. the points, lines, curves, surfaces or volumes. In this research, the detailed surface matching techniques will cover the 3D points with 3D structures, matching areas/regions/surfaces (piecewise segment matching of contours).
In Active Appearance Models, intensity matching (aka texture matching) is defined as matching the pixel intensity across the object with the correspondence intensity in another object (Steggmann et. al., 2000).
Discussion:
Here, all the above discussed matching methods will be proposed in the research.
References:
Stefman MB, Fisker R, Ersboll BK, Thodberg HH and Hyldstrup L (2000), Active Appearance Models: Theory and Cases, http://www2.imm.dtu.dk/~aam/main/node34.html (retrieved on the 10 may 2005).
Simon DA (1996), Fast and Accurate Shape-based Registration, PhD Thesis, Carnegie Mellon University, Pittsburgh, US
# posted by Jacey Lynn Minoi : 12:45 pm
