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This paper presents a multi-modal affect recognition system that is capable of effectively estimating human affective states through analyzing and fusing a number of non-invasive external cues. The proposed system consists of a probabilistic information fusion model based on the influence diagram and a set of data analysis, feature extraction and affect recognition modules for processing heterogeneous...
In this paper, we present a new method to modify the appearance of a face image by manipulating the illumination condition, when the face geometry and albedo information is unknown. This problem is particularly difficult when there is only a single image of the subject available. Recent research demonstrates that the set of images of a convex Lambertian object obtained under a wide variety of lighting...
For many computer vision problems, it is very important to produce the ground truth data. Manual data labeling is labor-intensive and prone to the human errors, whereas fully automatic data labeling is not feasible and reliable. In this paper, we propose an interactive labeling technique for efficient and accurate data labeling. Constructed on a Bayesian network (BN), the automatic image labeler produces...
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