I shortly will describe in this post, how we solved the problem of aligning landmarks of all face images for the RaFD. Making a database with really good alignment of eyes, nose etc. seemed germain to us, as for our own research we had to align the images of other databases regularly manually.
The problem
Even though we paid close attention to the positioning of our models during the photoshoot, the images throughout the session show considerable variation in positioning:
The solution
As you can imagine, doing a manual alignment for 17.000+ pictures is not really an option (and not really objective either). So we opted for an automated procedure for this and came up with a rather simple solution. We currently use the nonlinear general purpose fitting function 'fminsearch' from Matlab to optimize the correlation between a template and a target image. The optimization procedure varies two translational parameters (x-, and y-direction) plus one rotational parameter. For each iterative step, the correlation of template and target is calculated for a specific area of the images. fminsearch then varies those parameters until some matching criterion is met.
To see it working, look at this:
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1 comment:
Great post! And a movie even, impressive!
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