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Scientific VisualizationVolume 9, Issue 1, 2017, Pages 124-136

The technology of «computer vision» in the question of visual identification of a person(Article)

  • Kuznetsov, R.A.,
  • Ushakov, M.A.,
  • Maschenko, M.V.,
  • Volkova, E.A.
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  • Nizhny Tagil Socio-pedagogical Institute of Federal State Autonomous Educational Institution, Russian State Vocational Pedagogical University, Nizhny Tagil, Russian Federation

Abstract

Describes the results of work in the field of visual identification of the user using the application system. The detailed description of the structure of the system, its interface and painted the algorithm of the system, providing visual identification of the human face. In the basis of the presented algorithm in system identification LBPH, which is currently the most advanced in the field of two-dimensional identification of a facial image. Presented designed the class diagram of the system developed. Described algorithms of the system operation in the storage mode of the object and in the identification mode. Based on the developed class hierarchy and algorithms of the system was written in code in the programming language C ++. As a result, presented an application that creates a collection of training samples from a set of visual images of the object being initialized, and also produces the training of the machine learning algorithm and performs the visual identification of a person based on the vector model obtained by machine learning.

Author keywords

Application softwareComputer visionData analysisIdentificationVisualization

Indexed keywords

Engineering controlled terms:Application programsArtificial intelligenceC++ (programming language)Computer programmingData reductionData visualizationDigital storageFlow visualizationIdentification (control systems)Image processingLearning algorithmsLearning systems
Engineering uncontrolled termsApplication systemsClass diagramsClass hierarchiesFacial imagesSystem operationTraining sampleVector modelsVisual identification
Engineering main heading:Computer vision
  • ISSN: 20793537
  • Source Type: Journal
  • Original language: English
  • Document Type: Article
  • Publisher: National Research Nuclear University


© Copyright 2018 Elsevier B.V., All rights reserved.

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