A contrario detection of faces with a short cascade of classifiers
The a contrario framework has been successfully 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 obtains similar detection
rates than a classical (and longer) one at a much lower computational cost.
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 obtains similar detection
rates than a classical (and longer) one at a much lower computational cost.
Abstract
The a contrario framework has been successfully 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 obtains similar detection rates than a classical (and longer) one at a much lower computational cost.
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