AAM search and fitting
With our fresh new combined shape and texture model, we have found a nice way to describe how a face could change not only in shape but also in appearance. Now we want to find which set of p shape and λ appearance parameters will bring our model as close as possible to a given input image I(x). We could naturally calculate the error between our instantiated model and the given input image in the coordinate frame of I(x), or map the points back to the base appearance and calculate the difference there. We are going to use the latter approach. This way, we want to minimize the following function:
In the preceding equation,
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