Dense Feature Based Face Recognition from Surveillance Video using Convolutional Neural Network

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K. Suma, et. al.

Abstract

Face Recognition is a field of identifying the person from the facial features and has wide application range in security, human computer interactions, finance etc. In recent years, many researchers have developed different algorithms to identify the Faces from various illumination variations and Pose variation, but these two problems remain unsolved in Face Recognition (FR) field.


The Local Binary Pattern (LBP) has already proved its robustness in illumination variation. This paper proposes a four-patch Local Binary Pattern based FR utilizing Convolutional Neural Network (CNN) for identifying the Facial images from various illumination conditions and Pose variation.

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How to Cite
et. al., K. S. (2021). Dense Feature Based Face Recognition from Surveillance Video using Convolutional Neural Network. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(5), 1436–1449. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/2040
Section
Research Articles