2.2.3. FL

FL (Fast Localization) [34] is a method that combines a modification of the standard VJ algorithm with a component for localizing a salient facial landmark. An image is scanned with a cascade of binary classifiers that considers a set of reasonable positions and scales. Computing a data structure, such as integral images, an image pyramid, or HoG features, etc., is not required with this method. An image region is classified as having a face when all the classifiers are in agreement that the region contains one. At this stage, another ensemble calculates the position of each facial landmark point. Each binary classifier in the cascade is an ensemble of decision trees that have pixel intensity comparisons in their internal nodes as binary tests. Moreover, they are based on the same feature type, unlike the VJ algorithm that uses five types of Haar-like features. Learning takes place with a greedy regression tree construction procedure and a boosting algorithm.
