Learning based approach based on LEAR for facial fiducial point prediction of non-fronatal faces
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Date
2019
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UMT, Lahore
Abstract
Facial features points (FFP) are used for localization and representation of the prominent features of the face that are traced on tips, corners and mid-points of facial segments. The Proposed algorithm to detect facial landmarks on frontal and non-frontal face on video sequences. It syndicates regression based approach with advance block matching technique. In proposed methodology,it will be shown that how tree used to take estimate position of facial landmarks, straight from a scant subsection of pixel intensities with less time and by handling missing labeled data especially for non-frontal images. The Proposed algorithm, encompass the regression based model to provide a quality measure of each prediction and use the shape model to restrict and correct the sampling region. Our approach is extension of existing LEAR combines the low computational cost with selection of important features based on 22 facial points. The proposed algorithm is tested on five datasets. Results presented significant enhancement over the current state of the art.