Abstract

Proposed is a pixel-pattern-based texture feature (PPBTF) for realtime facial expression recognition. Grey-scale images are transformed into pattern maps where edges and lines are used for characterising facial texture. Based on the pattern map, a feature vector is constructed. Adaboost and a support vector machine (SVM) are adopted. Experiments on the Cohn-Kanade database illustrate that the PPBTF is effective and efficient for facial expression recognition.

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