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This paper explores recognition of human emotion through the hand gestures generated for particular emotion. In non-verbal reflection of an emotion hand generates various gestures using its most flexible parts viz. Fingers, Palm and Arm. In recognition process, an image or sequence of images of a hand gesture is first normalized before extracting the features from them. Thereafter, as a feature of these normalized gesture images, the Principle Components (PCs) of images are analysed. Furthermore, Neural Networks (NN), using Back Propagation Algorithm classifies the obtained PCs and finally the input gesture of an emotion is matched into the classes of pre stored trained hand gesture image sets of seven basic emotions Neutral, Happy, Sad, Fear, Anger, Disgust and Surprise.

Recognition of an Emotion using Principle Component Analysis of Hand Gesture of a Human