Article thumbnail
Location of Repository

Face recognition with independent component based super-resolution

By Aytül Erçil, Aytul Ercil, Osman Gökhan Sezer, Osman Gokhan Sezer, Yücel Altunbaşak and Yucel Altunbasak

Abstract

Performance of current face recognition algorithms reduces significantly when they are applied to low-resolution face images. To handle this problem, super-resolution techniques can be applied either in the pixel domain or in the face subspace. Since face images are high dimensional data which are mostly redundant for the face recognition task, feature extraction methods that reduce the dimension of the data are becoming standard for face analysis. Hence, applying superresolution in this feature domain, in other words in face subspace, rather than in pixel domain, brings many advantages in computation together with robustness against noise and motion estimation errors. Therefore, we propose new superresolution algorithms using Bayesian estimation and projection onto convex sets methods in feature domain and present a comparative analysis of the proposed algorithms with those already in the literature

Topics: TA Engineering (General). Civil engineering (General)
Publisher: SPIE
Year: 2006
DOI identifier: 10.1117/12.645868
OAI identifier: oai:research.sabanciuniv.edu:1163
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://research.sabanciuniv.ed... (external link)
  • http://research.sabanciuniv.ed... (external link)
  • http://dx.doi.org/10.1117/12.6... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.