Environment-adaptive multi-channel biometrics

The paper looks into multi-channel/multimodal biometric systems that are adaptive to environmental variations. We introduce a general formulation that addresses the environmental robustness of multi-channel fusion in biometric systems. Based on the formulation, two audio-visual biometric systems are developed. The first relies on confidence measures derived from environmental conditions to weight the contributions of the biometric channels dynamically; whereas the second considers the multiple channels jointly to adjust the fusion parameters optimally according to the current environmental conditions. Experimental evaluations with varying testing conditions show that both systems achieve lower recognition error rate compared with a baseline non-environment-adaptive audio-visual system. It is further shown that incorporating joint optimization of multichannel fusion parameters to cater to environmental changes, as in the second system, consistently leads to improved recognition accuracy over other systems, and, at the same time, it is guaranteed to perform no worse than any of the individual biometric channels under all environmental conditions.