Abstract
In this paper, we discuss an application of the linguistic descriptions obtained directly from experts’ and treated as the votes when characterizing facial images to carry out face classification. Despite various automated face recognition techniques, the expert’s opinion plays a pivotal role in making classification decisions when recognizing faces, say in problems of suspect identification. Here, we analyze the impact of critical factors (e.g., a number of experts, voting schemes, distance functions) and their impact on the performance of classification schemes. The well-established Analytic Hierarchy Process (AHP) is used to quantify importance of linguistic descriptors in the process of face recognition by humans. As a result we produce realistic weights improving the accuracy of classification. Experimental results are presented including a number of parametric studies.
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Acknowledgements
The authors are supported by National Science Centre, Poland (grant no. 2014/13/D/ST6/03244). Support from the Canada Research Chair (CRC) program and Natural Sciences and Engineering Research Council is gratefully acknowledged (W. Pedrycz).
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Karczmarek, P., Kiersztyn, A., Pedrycz, W., Dolecki, M. (2016). Linguistic Descriptors and Analytic Hierarchy Process in Face Recognition Realized by Humans. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9692. Springer, Cham. https://doi.org/10.1007/978-3-319-39378-0_50
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