Active Appearance Model (AAM) is a algorithm that uses a statistical model. This model is a model of the shape and grey-level appearance of an object. During the training phase of the algorithm, we begin to learn the relationship between model parameter displacements and the residual errors induced between a training image and a synthesised model. This algorithm is able to give a good overall match in just a few iterations even with poor starting estimates (to a certain degree).
However AAM is very sensitive to the initial matching position of the model and the image, and there could be problems with the computational expense of the algorithm and its accuracy without a good starting place.
References
T.F. Cootes, G.J. Edwards, C.J. Taylor. Active Appearance Models. 1998. Proc European Conference on Computer Vision.
(http://www.cs.cmu.edu/~efros/courses/AP06/Papers/cootes-eccv-98.pdf)
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