Fusing Biometric Scores using Subjective Logic for Gait Recognition on Smartphone

Abstract

The performance of a biometric system gets affected by various types of errors such as systematic errors, random errors, etc. These kinds of errors usually occur due to the natural variations in the biometric traits of subjects, different testing, and comparison methodologies. Neither of these errors can be easily quantifiable by mathematical formulas. This behavior introduces an uncertainty in the biometric verification or identification scores. The combination of comparison scores from different comparators or combination of multiple biometric modalities could be a better approach for improving the overall recognition performance of a biometric system. In this paper, we propose a method for combining such scores from multiple comparators using Subjective Logic (SL), as it takes uncertainty into account while performing to biometric fusion. This paper proposes a framework for a smartphone based gait recognition system with application of SL for biometric data fusion.