A feature information based approach for enhancing score-level fusion in multi-sample biometric systems

Sandeep Puthanveetil Satheesan, Sergey Tulyakov, Venu Govindaraju

Research output: Contribution to conferencePaperpeer-review

Abstract

Matching score fusion is a commonly used technique for improving the performance of biometric systems. In this paper we investigate the methods for fusing the scores obtained from matching individual video frames to a stored face template. Traditional fusion rules like sum and product does not account for the diversity of information contained in consecutive frames. Instead, we propose to use a quantitative measure of the shared information content between adjacent frame pairs to capture this information and enhance the score fusion performance. We conduct our experiments in a database of 132 person videos. The results show that application of information content to score level fusion can increase the performance of a fusion algorithm and hence make it more robust to errors. The developed matching score fusion method can be applied to other systems involving the multiple biometric samples or scans.

Original languageEnglish (US)
DOIs
StatePublished - 2013
Event2013 4th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, NCVPRIPG 2013 - Jodhpur, Rajasthan, India
Duration: Dec 18 2013Dec 21 2013

Conference

Conference2013 4th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, NCVPRIPG 2013
CountryIndia
CityJodhpur, Rajasthan
Period12/18/1312/21/13

Keywords

  • feature information content
  • Multi-biometrics
  • score-level fusion

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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