PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Estimating the Quality of Face Localization for Face Verification
Yann Rodriguez, Fabien Cardinaux, Johnny Mariéthoz and Samy Bengio
In: IEEE International Conference on Image Processing, ICIP, Oct 2004, Singapore.

Abstract

Face localization is the process of finding the exact position of a face in a given image. This can be useful in several applications such as face tracking or person authentication. The purpose of this paper is to show that the error made during the localization process may have different impacts depending on the final application. Hence in order to evaluate the performance of a face localization algorithm, we propose to {\em 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 on the BANCA database that our proposed measure best matches the final verification results when comparing several localization algorithms, on various performance measures currently used in face localization.

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EPrint Type:Conference or Workshop Item (Talk)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:171
Deposited By:Samy Bengio
Deposited On:03 June 2004