Title :
Face recognition using PCA and LDA: Analysis and comparison
Author :
Ravi, Siddarth ; Mankame, Dattatreya P. ; Nayeem, Sadique
Author_Institution :
Dept. of Comput. Sci., Pondicherry Univ., Pondicherry, India
Abstract :
Computer recognition of the human faces has evolved as the most successful and demanding field in the computer science world and in particular Computer Vision. A lot of research work has been done in this field in the last two decade. Numerous algorithms have been projected and they have been experimented with different face image database available. In this paper, a comparative study has been carried out using the two basic and the most important appearance based face recognition methods viz, PCA and LDA. These two techniques for face recognition has been implemented and evaluated with different databases like UMIST, Yale etc. The outputs are compared by using accuracy rate.
Keywords :
computer vision; face recognition; principal component analysis; LDA; PCA; UMIST database; Yale database; accuracy rate; computer vision; face image database; face recognition; linear discriminant analysis; principal component analysis; FERET; Face Recognition; LDA; ORL; PCA; Scatter Matrices;
Conference_Titel :
Communication and Computing (ARTCom 2013), Fifth International Conference on Advances in Recent Technologies in
Conference_Location :
Bangalore
Print_ISBN :
978-1-84919-842-4
DOI :
10.1049/cp.2013.2202
