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

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 accou...

Full description

Saved in:
Bibliographic Details
Main Authors: Puthanveetil Satheesan, Sandeep, Tulyakov, Sergey, Govindaraju, Venu
Format: Conference Proceeding
Language:English
Subjects:
Biometrics (access control)
Conferences
Face
Feature extraction
feature information content
Measurement
Multi-biometrics
score-level fusion
Silicon
Vectors
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
DOI:10.1109/NCVPRIPG.2013.6776242