Automatic Facial Expression Recognition Using Features of Salient Facial Patches


Extraction of discriminative features from salient facial patches plays a very important role in effective facial features recognition. The accurate detection of facial landmarks improves the localization of the salient patches on face images. This paper proposes a completely unique framework for expression recognition by using appearance options of selected facial patches. A few outstanding facial patches, relying on the position of facial landmarks, are extracted which are active during emotion elicitation. These active patches are more processed to get the salient patches that contain discriminative options for classification of every try of expressions, thereby selecting different facial patches as salient for various try of expression classes. One-against-one classification technique is adopted using these options. In addition, an automated learning-free facial landmark detection technique has been proposed, that achieves similar performances as that of alternative state-of-art landmark detection methods, nonetheless needs significantly less execution time. The proposed technique is found to perform well consistently in numerous resolutions, hence, providing a answer for expression recognition in low resolution pictures. Experiments on CK+ and JAFFE facial features databases show the effectiveness of the proposed system.

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