Multilevel Face Recognition System

The problem of biometric person identification on the basis of component-based face recognition is considered. It is shown that the face recognition system can be represented as a hierarchically organized multilevel system, in which an ensemble of local classifiers forms “soft” decisions about the i...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Cybernetics and systems analysis Ročník 60; číslo 1; s. 146 - 151
Hlavní autori: Opanasenko, V. M., Fazilov, Sh.Kh, Radjabov, S. S., Kakharov, Sh.S.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.01.2024
Springer Nature B.V
Predmet:
Algorithms
Artificial Intelligence
Biometric identification
Classifiers
Computer Engineering
Control
Cybernetics
Decision making
Decisions
Face recognition
Facial recognition technology
Informatics
Mathematics
Mathematics and Statistics
Multilevel
New Means of Cybernetics
Pattern recognition
Processor Architectures
R&D
Research & development
Software Engineering/Programming and Operating Systems
Systems Analysis
Systems Theory
classifier combination rule
classifier ensemble
multilevel recognition system
decision making
pattern recognition
ISSN:1060-0396, 1573-8337
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:The problem of biometric person identification on the basis of component-based face recognition is considered. It is shown that the face recognition system can be represented as a hierarchically organized multilevel system, in which an ensemble of local classifiers forms “soft” decisions about the images of individual components of a face belonging to given classes. Then, based on the integration of these decisions, the final decision on whether the recognized face belongs to one of the given classes is formed. The problems of constructing a local classifier model, as well as choosing an integrator of intermediate solutions of local classifiers, are formulated and solved.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1060-0396
1573-8337
DOI:10.1007/s10559-024-00655-w