Real-time face identification from video surveillance cameras

Diego Acuña-Escobar, Julio Ibarra-Fiallo, Monserrate Intriago-Pazmiño

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this research work, we present the implementation of a web environment and processing core based on convolutional neural networks, to recognize faces in real time. The environment can work with several video surveillance cameras at the same time. We conclude that ten images of a person are required for recognition to be highly reliable. The environment was tested with 32 volunteers, in 4 different environments: front face, smiling, wearing a cap, and glasses. We obtained 94%, 91%, and 90% in metrics true-positive-rate, precision, and accuracy, respectively.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Data Science, E-Learning and Information Systems, DATA 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450372848
DOIs
StatePublished - 2 Dec 2019
Event2nd International Conference on Data Science, E-Learning and Information Systems, DATA 2019 - Dubai, United Arab Emirates
Duration: 2 Dec 20195 Dec 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2nd International Conference on Data Science, E-Learning and Information Systems, DATA 2019
Country/TerritoryUnited Arab Emirates
CityDubai
Period2/12/195/12/19

Keywords

  • Convolutional neural network
  • Deep learning
  • Face recognition
  • People identification

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