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计算机科学技术学报 2009
Facial Expression Recognition of Various Internal States via Manifold LearningKeywords: manifold learning,locally linear embedding,dimension model,pleasure-displeasure dimension,arousal-sleep dimension Abstract: Emotions are becoming increasingly important in human-centered interaction architectures.Recognition of facial expressions,which are central to human-computer interactions,seems natural and desirable.However,facial expressions include mixed emotions,continuous rather than discrete,which vary from moment to moment.This paper represents a novel method of recognizing facial expressions of various internal states via manifold learning,to achieve the aim of humancentered interaction studies.A critical review of ...
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