An SVD based common matrix method for face recognition: Single image per person

Apaydin M., TURHAL Ü. Ç., Duysak A.

25th International Symposium on Computer and Information Sciences, ISCIS 2010, London, England, 22 - 24 September 2010, vol.62 LNEE, pp.289-292, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 62 LNEE
  • Doi Number: 10.1007/978-90-481-9794-1_55
  • City: London
  • Country: England
  • Page Numbers: pp.289-292
  • Keywords: Common Matrix (CM), Common vector (CV) approach, Face recognition, Single training image per person, Singular value decomposition (SVD)
  • Bilecik Şeyh Edebali University Affiliated: Yes

Abstract

Common Matrix (CM) fails to work when there is only one image available in the training set. In this paper, an approach to solve this problem is proposed. By using singular value decomposition (SVD) null space of the image matrices are obtained. By projecting the image matrix onto the null space, common matrices are obtained for each class. After obtaining the common matrices, optimal projection vectors will be those that maximize the total scatter of the common matrices. © 2011 Springer Science+Business Media B.V.