2.2.1. VJ

The canonical VJ algorithm [14] is based on Haar wavelets extracted from the integral image. Classification is performed, as noted in the introduction, by combining an ensemble of AdaBoost classifiers that select a small number of relevant descriptors with a cascade combination of weak learners.

The disadvantage of this approach is that it requires considerable training time. However, it is relatively fast during the testing phase. The precision of VJ relies on the threshold *s*, which is used to classify a face within an input subwindow.
