Estimating the quality of face localization for face verification

Face localization is the process of finding the exact position of a face in a Liven image. This call be Useful in several applications such as face tracking or person authentication. The Purpose of this paper is to show that the cri-or made during the localization process may have different impacts depending oil the final application. Hence in order to evaluate the performance of a face localization algorithm, we propose to embed the final application (here face verification) into the performance measuring Process. Moreover, in this paper. we estimate this embedding using either a multilayer perceptron or a K nearest neighbor algorithm in order to speedup the evaluation process. We show oil the BANCA database that our proposed measure best matches the final verification results when comparing several localization algorithms, oil various performance measures Currently used in face localization.