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Recognizing facial actions from spontaneous facial displays suffers from subtle and complex facial deformation, frequent head movements, and partial occlusions. It is especially challenging when the facial activities are accompanied with speech. Instead of employing information solely from the visual channel, this paper presents a novel fusion framework, which exploits information from both visual...
Face registration is a major and critical step for face analysis. Existing facial activity recognition systems often employ coarse face alignment based on a few fiducial points such as eyes and extract features from equal-sized grid. Such extracted features are susceptible to variations in face pose, facial deformation, and person-specific geometry. In this work, we propose a novel face registration...
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...
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