Automated Real-Time Face Recognition and Tagging

Authors(3) :-Kumaran U, Poonaganti Preethi, R Dimple Janani

This paper mainly addresses the building of facial recognition software which falls into a large group of technologies known as biometrics. It has been one of the most interesting and important research fields. The methods may vary, but they generally involve a series of steps that serve to capture, analyze and compare your face to a database of stored images. For automatically identifying or verifying a person from a digital image or a video source, there is a need for an automated face recognition system. One of the ways to do this is by comparing selected features of the faces from the image and the database of several faces. Automatic face detection is a complex problem in real-time video processing. This problem is commonly referred to as face location, face extraction, or face segmentation. This paper presents a new algorithm to automatically segment out and recognize a person’s face from a real-time video and the main objective is to tag the faces accordingly by comparing the facial features from the existing dynamic database. By using this technique a large number of individuals or a group of people can get benefited. This is the reason which is responsible for a great need in the field of facial recognition.

Authors and Affiliations

Kumaran U
Assistant Professor Senior, Department of Systems & Software Engineering, VIT, Vellore, Tamil Nadu, India
Poonaganti Preethi
Department of Systems & Software Engineering, VIT, Vellore, Tamil Nadu, India
R Dimple Janani
Department of Systems & Software Engineering, VIT, Vellore, Tamil Nadu, India

Face detection, Face recognition, Feature Extraction, Eigen face, Eigenvector, Haar-like features, PCA, LDA, ICA, MCPA, LPP, Feature selection, Dimension reduction, Covariance.

  1. A J. Goldstein, L. D. Harmon, and A. B. Lesk, “Identification of Human Faces,” Proc. IEEE, Vol. 59, No. 5, 748-760, May 1971.
  2. “Face Recognition from Group Photograph”, KavitaShelke, International Journal of Engineering and Innovative Technology (IJEIT), Volume 3, Issue 1, July 2013
  3. “Semi-automatic photograph tagging by combining context with content based information” , Hugo Feitosa de Figueirêdo, Claudio de Souza Baptista, Marco Antonio Casanova, Tiago Eduardo da Silva, Anselmo Cardoso de Paiva
  4. P Viola and M. J. Jones, Robust real-time face detection, International Journal of Computer Vision, 57 (2004), pp. 137-154, 2004.
  5. Image-based Face Detection and Recognition: “State of the Art” Faizan Ahmad, AaimaNajam, Zeeshan Ahmed, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 6, No 1, November 2012.
  6. An Analysis of the Viola-Jones Face Detection Algorithm Yi-Qing Wang CMLA, ENS Cachan, France “Face Recognition”, FDI of USA
  7. DIGITAL IMAGE PROCESSING, 3rd Edition, Gonzalezby Pearson Education, Inc.
  9. http://in.mathworks.c

Publication Details

Published in : Volume 4 | Issue 6 | May-June 2018
Date of Publication : 2018-05-08
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 405-409
Manuscript Number : CSEIT184676
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Kumaran U, Poonaganti Preethi, R Dimple Janani, "Automated Real-Time Face Recognition and Tagging", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 6, pp.405-409, May-June-2018.
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