Modular Common Vector Approach


KOÇ M., BARKANA A.

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 23 - 25 April 2014, pp.533-535 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2014.6830283
  • City: Trabzon
  • Country: Turkey
  • Page Numbers: pp.533-535
  • Keywords: common vector approach, face recognition, occlusion, FACE RECOGNITION, OCCLUSION
  • Anadolu University Affiliated: Yes

Abstract

The performance of a face recognition system is negatively affected by the accessories used on the face Like many methods, the recognition performance of the Common Vector Approach (CVA) [1] over occluded images is not at the desired level. In this work, we proposed an extension of the CVA, namely the Modular Common Vector Approach (M-CVA), which improves the recognition performance at the occluded face images. M-CVA outperforms CVA by a margin of 82,7 percent in the experiments which are conducted over AR face database.