Abstract
The problem of constructing a supervised local classifier is solved in this article. In essence, this task is a classical recognition problem. The mathematical formulation and method of solving the problem, the results of experimental studies, as well as a detailed description of the main stages of building a local classifier, based on the assessment of the interdependence between fragments (face components) of the image of a recognizable face, are given. This article also discusses local face recognition methods based on the analysis of face components. A new approach to component-based face recognition is proposed, which (compared with existing analogs) has a number of advantages, the main of which is that when using local classifiers, it is possible to make soft decisions presented in the form of a list of candidates with weights assigned to them. The acceptance of such decisions ensures the stability of the system.
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Fazilov, S.K., Mirzaev, O.N., Kakharov, S.S. (2023). Building a Local Classifier for Component-Based Face Recognition. In: Zaynidinov, H., Singh, M., Tiwary, U.S., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2022. Lecture Notes in Computer Science, vol 13741. Springer, Cham. https://doi.org/10.1007/978-3-031-27199-1_19
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