Abstract
This paper presents a concept of optimizing parameters used for solving image identification tasks developed during research aimed at improving recognition of human face images. Effectiveness of closed-set identification is measured in a form of Total Classification Error (TCE) which can be expressed as a function of parameters used for calculating similarity between samples. TCE can be minimized for a defined training set in order to obtain optimal values of the parameters. This method was implemented to optimize face relevance maps applied to improve the Eigenfaces method for human face recognition. Results of the experiments presented in this paper confirm effectiveness of the developed approach.
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Kawulok, M. (2008). Optimization of Face Relevance Maps with Total Classification Error Minimization. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_93
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DOI: https://doi.org/10.1007/978-3-540-69812-8_93
Publisher Name: Springer, Berlin, Heidelberg
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