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Multi-modal biometric fusion is more accurate and reliable compared to recognition using a single biometric modality. However, most existing fusion approaches neglect the influence of the qualities of the biometric samples in information fusion. Our goal is to advance the state-of-the-art in biometric fusion technology by providing a more universal and more accurate solution for personal identification...
Graphical models such as Bayesian networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model parameters often requires a large amount of reliable and representative training data, which proves to be difficult to acquire for many computer vision tasks. On the other hand, there is often available qualitative prior knowledge...
A system that could automatically analyze the facial actions in real time has applications in a wide range of different fields. However, developing such a system is always challenging due to the richness, ambiguity, and dynamic nature of facial actions. Although a number of research groups attempt to recognize facial action units (AUs) by improving either the facial feature extraction techniques or...
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