An online facial expression recognition system based on personalized galleries is presented. This system is built on the framework of the PersonSpotter system, which is able to track and detect the face of a person in a live video sequence. By utilizing the recognition method of Elastic Graph Matching, the most similar person whose images are stored in the gallery can be found, then the personalized gallery of this person is used to recognize the expression on the probe face. A personalized gallery consists of images of the same person showing different facial expressions. Node weighting and weighted voting in addition to Elastic Graph Matching are applied to identify the expression. The performance achieved by this system shows its great potential.
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