Recognition of Face and Gait

S. Jeba Shiny*
Department of Computer Science and Engineering, DMI Engineering College, Aralvaimozhi, Tamil Nadu, India.
Periodicity:July - December'2021
DOI : https://doi.org/10.26634/jpr.8.2.18149

Abstract

The recognition accuracy of 3 face recognition algorithms supported in mathematical spaceways (i.e., the Eigenfaces approach, the Fisher Faces technique, and the probabilistic Eigenfaces approach) is tested for various gallery sizes, image resolutions, and ranges of bits per pixel. Identical experiments are then conducted for numerous mixtures of these techniques, and the effectiveness of these mixtures is compared with that of the individual methods. The results show that there are some interesting relationships between recognition accuracy and image resolution. They also show that the mixtures of these techniques do improve performance over the individual approaches, which suggests that it might be worth looking into the unification of these approaches.

Keywords

Face Recognition, Principal Component Analysis (PCA), Eigenfaces, FisherFaces.

How to Cite this Article?

Shiny, S. J. (2021). Recognition of Face and Gait. i-manager's Journal on Pattern Recognition, 8(2), 37-45. https://doi.org/10.26634/jpr.8.2.18149

References

[12]. Turk, M. (1991). A Pentland Eigenfaces for Recognition. Journal of Cognitive Neuroscience, 3(1), 71-86.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Online 15 15

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.