Most work on multi-biometric fusion is based on static fusion rules. One prominent limitation of static fusion is that it cannot respond to the changes of the environment or the individual users. This paper proposes context-aware multibiometric fusion, which can dynamically adapt the fusion rules to the real-time context. As a typical application, the context-aware fusion of gait and face for h...

Gait and face are two important biometrics for human identification. Complementary properties of these two biometrics suggest fusion of them. The relationship between gait and face in the fusion is affected by the subject-to-camera distance. On the one hand, gait is a suitable biometric trait for human recognition at a distance. On the other hand, face recognition is more reliable when the subj...

The quality of biometric samples used by multimodal biometric experts to produce matching scores has a significant impact on their fusion. We address the problem of quality controlled fusion of multiple biometric experts and focus on the fusion problem in a scenario where biometric trait quality expressed in terms of quality measures can be coarsely quantised. We develop a fusion methodology ba...