Sparse random projection for efficient cancelable face feature extraction

Youngsung Kim, Kar Ann Toh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Based on a recently proposed framework for cancelable biometric template generation, this paper focuses on boosting the computational efficiency using a sparse random projection. Comparing with a non-sparse random projection, we show empirically that the verification accuracy of templates generated by sparse random projection do not degrade while enjoying a more efficient feature extraction process than before. This work contributes to establishment of an algorithm for effective cancelable face template generation.

Original languageEnglish
Title of host publication2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Pages2139-2144
Number of pages6
DOIs
Publication statusPublished - 2008
Event2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 - Singapore, Singapore
Duration: 2008 Jun 32008 Jun 5

Publication series

Name2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

Other

Other2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
CountrySingapore
CitySingapore
Period08/6/308/6/5

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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  • Cite this

    Kim, Y., & Toh, K. A. (2008). Sparse random projection for efficient cancelable face feature extraction. In 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 (pp. 2139-2144). [4582897] (2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008). https://doi.org/10.1109/ICIEA.2008.4582897