Comparison of matrix decomposition and SIFT descriptor based methods for face alignment

Yalcin M., YAVUZ H. S.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16 - 19 May 2016, pp.1841-1844, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2016.7496121
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.1841-1844
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

Face alignment is an important pre-processing step for face analysis systems. Especially, the performance of face recognition systems can be improved by using aligned face images. In this work, we used matrix decomposition based and SIFT features based methods in face alignment. We performed recognition experiments by using raw versus aligned images with an image set based classification method. We also developed a SIFT-flow based affine transformation and showed that this type of alignment improves the recognition accuracies.