Are Object Recognition Models Effective and Unbiased for Biometric Recognition?

Can the general-purpose pre-trained image classifier be effective for biometric recognition? Due to the prevalence of generic features in these models, we assert that they can be used to extract the discriminating feature of the biometrics images which help encode the object images. The utilization of features from the pre-trained model can significantly limit the training requirements and can be deployed on computationally limited devices. In this research, we have conducted an extensive study to perform biometric recognition using existing state-of-the-art pre-trained deep neural networks. The experiments are not limited to any modality or imaging spectrum to ensure the findings are trustworthy and thorough. The experiments conducted on various modalities including multi-modal biometric recognition as well showcase that the pre-trained deep networks can be a suitable option for cost-effective biometric recognition. Further, we have also evaluated the fusion of deep neural networks to see if the performance can further be improved without significantly increasing the computational cost.