An ensemble learning approach to lip-based biometric verification, with a dynamic selection of classifiers

We have shown that the competence of the base classifiers can be successfully calculated even if the number of their learning examples was limited. Such a situation is particularly observed with biometric data. In this paper, we propose a new biometric data structure, the Sim coefficients, along with an efficient data processing technique involving a pool of competent classifiers chosen by dynamic selection.