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Feature extraction is the most significant step in the operation of emotion expressions recognition. Discrimination operation of emotion expressions has gained the attention of many researchers in the field of pattern recognition because of its significant impact on the various aspects of applications, especially in the application of human-computer interaction, both for the image or to the video. Based on pattern recognition theory, the process of facial expression recognition can be divided into features extraction operation and classification operation. In this paper, the geometric-based features extraction operation is used for extracting the local characteristics (landmarks) of a set of emotion expressions (anger, happiness, sadness, surprise) for images of BOSPHORUS database as training stage, then the classification operation is done by using of the threshold method (Euclidean distance) between the distances of neutral image and the expression image. The trained system is used for feature extraction and classification for 3D video film (stereoscopic) as testing stage. This method is implemented on 40 3D video films that were recorded, 10 video films for each expression of the four basic emotion; the ratio of discrimination is 85%.

Geometric-based Feature Extraction and Classification for Emotion Expressions of 3D Video Film