Active Shape Models vs Active Appearance Models

Question

I am implementing active ASM/AAM using OpenCV for segmentation of face images using OpenCV (to be further used in face recognition). I am pretty much done with the canonical implementation of ASM (as per T. Cootes papers) and result I get is not ideal, it does not always converge and when it does some boundaries are not captured, which I believe is a problem in the modeling of a local structure - i.e. gradient profile matching.

Now I am a bit unsure what to do next. ASM is a simpler and computationally less intensive algorithm compared to AAM. Should I continue improving ASM(say for example using 2D profiles rather than 1D profiles, or use different profile structure for different type of lanmarks) or get my hands straight on AAM?

Edit: Also, what are the papers you could recommend that improve on the original work by T.Cootes? I know there are so many of them, but maybe there are techniques that are considered canonical today?

Answer 1

You can find clarifications and implemented AAM whith 2D profiles in the book "Mastering OpenCV with Practical Computer Vision Projects" by Packt Publishing 2012. A lot of projects described in this book are open source and can be downloaded here: GitHub. They are more advanced than T.Cootes implementation.

I can say that AAM (as existing implementation you can look also at vosm) have good convergence (better than ASM) only if you train it on the same man (very good results for example for FRANCK (Talking Face Video) sequence) in other cases ASM works better.