Tian-Xiang Wu

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In this paper, we propose a multi-view gender classification system with a hierarchical framework using facial images as input. The front end of the framework is a classifier, which will properly divides the input images into several groups. To ease the data sparsity problem in the multi-view scenario, facial symmetry is used to reduce the number of views.(More)
In this paper, we propose a novel system to analyze vigilance level combining both video and Electrooculography (EOG) features. For one thing, the video features extracted from an infrared camera include percentage of closure (PERCLOS) and eye blinks, slow eye movement (SEM), rapid eye movement (REM) are also extracted from EOG signals. For another, other(More)
In this paper, we propose a hierarchical classifier structure for gender classification based on facial images by reducing the complexity of the original problem. In the proposed framework, we first train a classifier, which will properly divide the input images into several groups. For each group, we train a gender classifier, which is called expert. These(More)
BACKGROUND Reinnervation of the facial musculature when there is loss of the proximal facial nerve poses a difficult clinical problem. Restoration of spontaneous mimetic motion is the aim and, to this end, the use of cross-facial nerve grafts has long been considered the reconstruction of choice. The nerve to masseter has been used very successfully for(More)
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