Face Recognition using Eigenvector and Principle Component Analysis

  title={Face Recognition using Eigenvector and Principle Component Analysis},
  author={D. Chakraborty and S. Saha and M. Bhuiyan},
  journal={International Journal of Computer Applications},
Face recognition is an important and challenging field in computer vision. [...] Key Method Various symmetrization techniques are used for preprocessing the image in order to handle bad illumination and face alignment problem. We used Eigenface approach for face recognition. Eigenfaces are eigenvectors of covariance matrix, representing given image space. Any new face image can then be represented as a linear combination of these Eigenfaces. This makes it easier to match any two given images and thus face…Expand
5 Citations
Towards Face Recognition Using Eigenface
  • 6
  • PDF
Face Recognition Analysis Using PCA, ICA And Neural Network
  • 3
Side View Face Identification Based on Wavelet and Random Forest
  • PDF


A feature based approach to face recognition
  • 383
  • Highly Influential
  • PDF
Eigenfaces for Recognition
  • 14,678
  • Highly Influential
  • PDF
Human face profile recognition by computer
  • 112
  • Highly Influential
The Automatic Recognition of Human Faces from Profile Silhouettes
  • 90
  • Highly Influential
Machine identification of human faces
  • 171
  • Highly Influential
Face recognition using a digital neural network with self-organising capabilities
  • M. A. Kerin, T. Stonham
  • Computer Science
  • [1990] Proceedings. 10th International Conference on Pattern Recognition
  • 1990
  • 17
Automatic recognition of human face profiles
  • 114
  • Highly Influential
Feature extraction from faces using deformable templates
  • 1,496
  • Highly Influential
Identification of human faces based on isodensity maps
  • 131
  • Highly Influential
Identification of human faces
  • 319
  • Highly Influential