TrainingAn appearance-based model of the pattern of interest (in this case, an eye) is encoded as a vector of Gabor responses.
This realistically involves averaging over a certain number of subjects (the training set).
More generally, response vectors from the images in the training set could be used to train a classifier.
SearchWhen looking from the pattern on a new image, a Gabor feature vector is extracted at each point.
The vector is compared against the model. The resulting distance map is expected to have a minimum at the location of the pattern we are looking for, were the feature vector best resembles the model.
Here again, the distance map could represent the output of a classifier rating each image pixel.
This common algorithm as it stands is therefore ill-suited for active vision applications.
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