AUTOMATIC DETECTION OF SMILING FACE AND NEUTRAL FACE
Authors: Sreelekshmi A.N
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Facial feature points, such as the corners of the eyes, corners and outer mid points of the lips and nostrils, are generally referred to as facial salient points. Detection of facial feature points is often the first step in computer vision applications such as face identification, facial expression recognition, face tracking and lip reading etc. Facial features generally include salient points which can be tracked easily, like corners of the eyes, nostrils, lip corners etc. Currently, most of the applications for facial expressions tracking are manually giving points as initial feature points for tracking. Detection of facial features like eye, pupil, mouth, nose, nostrils, lip corners, eye corners etc., with different facial expression and illumination is a challenging task. In the present work, human eye detection is the first step in facial feature detection, since the face has a nice facial geometry, which can be estimated, based on the eyes position. . In this work, we propose expression identification based on fully automatic detection of facial features and deals with the development of a technique that can perform the classification of given a frontal face input image, identify the features and classify the face into either neutral or smiling.
KEYWORDS- Face detection, Feature extraction, , ROI,Expression classification, Shi-Tomasi’s corner detection,Ada-boost algorithm, Haar-like features.