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Erschienen in: Soft Computing 17/2017

02.03.2016 | Methodologies and Application

A face recognition system based on convolution neural network using multiple distance face

verfasst von: Hae-Min Moon, Chang Ho Seo, Sung Bum Pan

Erschienen in: Soft Computing | Ausgabe 17/2017

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Abstract

The recognition technology that recognizes or discriminates certain individuals is very important for the security that provides intelligence services. Face recognition rate can vary depending on variability of the face itself as well as other external factors such as illumination, background, angle and distance of a camera position. The paper suggests a proper method for long-distance face recognition by resolving the change in recognition rate resulting from distance change in long-distance face recognition. For the long-distance face recognition test, face images by actual distance from 1 to 9 m away were obtained directly. Actual face images taken by distance were applied to resolve the issue rising from distance change and CNN was applied to extract overall features of face. The test showed that proposed face recognition algorithm that used CNN as feature extraction and face images by actual distance for training was found to show the best performance.

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Metadaten
Titel
A face recognition system based on convolution neural network using multiple distance face
verfasst von
Hae-Min Moon
Chang Ho Seo
Sung Bum Pan
Publikationsdatum
02.03.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 17/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-016-2095-0

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