Title :
Rational Value Sequence based Singular Value Decomposition for facial recognition
Author :
Shidaganti, Ganeshayya I. ; Chickerur, Satyadhyan
Author_Institution :
Dept. of Inf. Sci. & Eng., Sambhram Inst. of Technol., Bangalore, India
Abstract :
Various prominent feature points of human faces play a critical role for designing a system that can perform facial recognition. Involvement of facial expression as precision parameter exponentially increases the challenges in developing a face recognition system. There exist abundant volume of studies in the area of face recognition, but majority of the techniques are either computationally not viable or uses complex algorithms. Hence, the prime aim of this paper is to introduce a very simple and cost effective solution for face recognition system from facial expressions by using two techniques i.e. Singular Value Decomposition (SVD) and Rational Value Sequence based Singular Value Decomposition (RSVD). Results were evaluated for both the cases to find RSVD approach as a better alternative to SVD approach for face recognition in terms of preciseness and computational effectiveness.
Keywords :
face recognition; feature extraction; image classification; principal component analysis; singular value decomposition; PCA; RSVD; face recognition system; facial expression; facial recognition; feature points; human face; image classification; precision parameter; principal component analysis; rational value sequence based singular value decomposition; Algorithm design and analysis; Classification algorithms; Face recognition; Image recognition; Matrix decomposition; Principal component analysis; Singular value decomposition; Facial Recognition; Principal Component Analysis; Rational Value sequence based singular value decomposition; Singular Value Decomposition;
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4799-2432-5
DOI :
10.1109/ICACCI.2013.6637309