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Disguised Face Identification Using Face Graph and SVM Classifier

Published: 20 October 2015 Publication History

Abstract

In this paper, we describe disguised face identification using facial recognition technology in that Gabor feature on optimal face graph has extracted. Support vector machine (SVM) classifier recognizes a disguised face by employing the extracted Gabor feature from the estimated facial feature point, which composes an optimal face graph of a disguised face. The proposed disguised face identification system has been trained using various face samples, which have captured under unconstrained environment such as uncontrolled lighting condition or complex background and wearing a mask or a sunglass.

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  • (2022)Synthetic Occluded Masked Face Recognition using Convolutional Neural Networks2022 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)10.1109/IAICT55358.2022.9887517(124-129)Online publication date: 28-Jul-2022

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cover image ACM Other conferences
BigDAS '15: Proceedings of the 2015 International Conference on Big Data Applications and Services
October 2015
321 pages
ISBN:9781450338462
DOI:10.1145/2837060
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 October 2015

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Author Tags

  1. Disguised face identification
  2. Face graph
  3. Gabor feature
  4. SVM

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  • (2022)Synthetic Occluded Masked Face Recognition using Convolutional Neural Networks2022 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)10.1109/IAICT55358.2022.9887517(124-129)Online publication date: 28-Jul-2022

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