I’ve been a lot of research lately about the best way to detect and track face features such as noise, eye, noise, etc.. My initial thought was to use the same technique ubiquitously used for face detection, Viola-Jones object detection framework. The latter works great for face detection and can easily be tested in the examples provided in Opencv. Although, Opencv provides haarcascade_eye.xml for eye detection and another one for the mouth, the results were pretty disappointing even in trying to find the bounding box and not the contour of those features, which what we ultimately trying to achieve.
After few hours of searching and digging online, I came across a very promising technique called Active Appearance Model, created by Timothy Cootes from Manchester University.
He describes his technique with the following:
“The Active Appearance Model (AAM) is a generalisation of the widely used Active Shape Model approach, but uses all the information in the image region covered by the target object, rather than just that near modelled edges.An AAM contains a statistical model of the shape and grey-level appearance of the object of interest which can generalise to almost any valid example. Matching to an image involves finding model parameters which minimise the difference between the image and a synthesised model example, projected into the image. The potentially large number of parameters makes this a difficult problem.
We observe that displacing each model parameter from the correct value induces a particular pattern in the residuals. In a training phase, the AAM learns a linear model of the relationship between parameter displacements and the induced residuals. During search it measures the residuals and uses this model to correct the current parameters, leading to a better fit. A good overall match is obtained in a few iterations, even from poor starting estimates.”
Tim was kind enough to provide tools and toys that we can play with to understand the AAM. These toys can be found here. You might notice that there is no source code provided. If you are looking for source code for AAM, you would definitely want to check out Mikkel B. Stegmann’s site fully dedicated to AAM with an open source library. The site can be found here.
I also found a great project using ASM here and another one that uses AAM here. And a great opensource one here
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