Detection of facial features using statistical machine learning
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Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Classification modules can be used in multiple and diverse applications. The general objective of this work is the classification of facial features using statistical learning algorithms, this means being able to detect and classify the largest possible number of features that can be found on a face using only examples of images of these, without using a priori no information of the given characteristics. In the present work, detectors and classifiers of the characteristics that are considered most significant were developed, Excellent results were reported in mouth detection, with detection rates greater than 99% and errors comparable to the error from manual mouth marking. The lens sorter also obtained excellent results, with detection rates of 95% for databases with controlled environments and of the order of 90% for databases with uncontrolled environments. Beard and mustache classifiers after using the mouth detector obtained very good results, with a detection rate of over 95% in databases with uncontrolled environments. © 2020 IEEE.
Açıklama
4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 -- 22 October 2020 through 24 October 2020 -- -- 165025
Anahtar Kelimeler
Classification, Face Recognition, Machine Learning, Statistical Learning
Kaynak
4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 - Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
