Title of article :
A comprehensive experimental comparison of the aggregation techniques for face recognition
Author/Authors :
Karczmarek, P Institute of Institute of Computer Science - Lublin University of Technology, 20-618 Lublin, Poland , Pedrycz, W Department of Electrical & Computer Engineering - University of Alberta, Edmonton T6R 2V4 AB, Canada , Kiersztyn, A Institute of Institute of Computer Science - Lublin University of Technology, 20-618 Lublin, Poland , Dolecki, M Institute of Institute of Computer Science - Lublin University of Technology, 20-618 Lublin, Poland
Abstract :
In face recognition, one of the most important problems to tackle is a large amount of data and the redundancy of
information contained in facial images. There are numerous approaches attempting to reduce this redundancy. One
of them is information aggregation based on the results of classiers built on selected facial areas being the most
salient regions from the point of view of classication both by humans and computers. In this study, we report on
a series of experiments and oer a comprehensive comparison between various methods of aggregation of outputs of
these classiers based on essential facial features such as eyebrows, eyes, nose, and mouth areas. For each of them,
we carry the recognition process utilizing the well-known Fisherfaces transformation. During the comparisons of the
vectors representing the features of images (faces) after the transformations, we consider 16 similarity=dissimilarity
measures for which we select the best aggregation operator. The set of operators to compare was selected on a basis of
the comprehensive literature review regarding aggregation functions.
Keywords :
information aggregation , similarity=dissimilarity measures , facial features , aggregation functions , Face recognition
