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In this paper, we proposes an effective and novel approach to recognize subtle facial expression method which is facial expression deformation. The proposed method deforms subtle facial expressions into corresponding extreme facial expressions. Facial expression deformation processes by extracting subtle motion vector of the predefined feature points and amplifying them. By adding amplified motion vector to Active Appearance Models (AAMs) fitted feature points, the extreme facial expression images is recovered (obtained) by the piece-wise affine warping. After facial expression deformation, we extract the shape and appearance features by projecting deformed facial expression image to the AAM shape and appearance model. We use the multi-class Support Vector Machines (SVMs) to classify the shape and appearance features. The facial expression recognition performance shows promising results of the proposed method.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |