Efficient Focusing and Face Detection

We present an algorithm for shape detection and apply it to frontal views of faces in still grey level images with arbitrary backgrounds. Detection is done in two stages: (i) “focusing,” during which a relatively small number of regions-of-interest are identified, minimizing computation and false negatives at the (temporary) expense of false positives; and (ii) “intensive classification,” during which a selected region-of-interest is labeled face or background based on multiple decision trees and normalized data. In contrast to most detection algorithms, the processing is then very highly concentrated in the regions near faces and near false positives.