Survey on SVM Based Method for Identification and Recognition of Faces by Using Feature Distances

EasyChair Preprint 2082

Abstract

Support vector machine is a machine learning algorithm that has been developing since the mid-1990s. There are two significant things in face recognition using SVM. One is the component feature extraction from images, the other is the classifier we choose. The relative distance between the features of face is used to uniquely identify a person. These measures are used to train the SVM and the closest match with the input data is results in a successful identification. Minimum distance classifier is used for identification process.

Keyphrases: SVM, face recognition, feature extraction, machine learning

@booklet{EasyChair:2082,
  author    = {Piyush Choudhary and Poorva Agrawal and Gagandeep Kaur},
  title     = {Survey on SVM Based Method for Identification and Recognition of Faces by Using Feature Distances},
  howpublished = {EasyChair Preprint 2082},
  year      = {EasyChair, 2019}}