A Contrario Detection of Faces with a Short Cascade of Classifiers
Jose-Luis Lisani, Silvia Ramis
⚠ This is a preprint. It may change before it is accepted for publication.


The a contrario framework has been succesfully used for the detection of lines, contours and other meaningful structures in digital images. In this paper we describe the implementation of an algorithm for face detection published in 2017 by Lisani et al. which applies the a contrario approach to the computation of the detection thresholds of a classical cascade of classifiers. The result is a very short cascade which improves the detection rates of a classical (and longer) one at a much lower computational cost.