Age estimation and face verification across aging using landmarks

Tao Wu, Pavan Turaga, Rama Chellappa

Research output: Contribution to journalArticlepeer-review

79 Scopus citations


Age estimation and face verification across aging are important problems with a wide range of applications. It is well known that age and identity information are encoded in both texture and shape of the face. Building on recent advances in landmark extraction and statistical techniques for landmark-based shape analysis, we consider these problems using facial shapes. We show that by using well-defined shape spaces and their associated geometry, one can obtain significant performance improvements in both age estimation and face verification. Toward this end, we propose to model the facial shapes as points on a Grassmann manifold. Age estimation and face verification are then considered as regression and classification problems on this manifold. Algorithms for regression and classification are designed to take into account the geometry of the underlying space. The proposed method is flexible and can be used as a standalone age estimator or classifier, and we also present methods for fusion with texture-based algorithms.

Original languageEnglish (US)
Article number6272347
Pages (from-to)1780-1788
Number of pages9
JournalIEEE Transactions on Information Forensics and Security
Issue number6
StatePublished - 2012


  • Age estimation
  • Grassmann manifold
  • biometrics
  • face verification
  • facial shapes

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications


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