AGE GROUP CLASSIFICATION USING FACE FEATURES
Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.6, No. 2)Publication Date: 2017-03-02
Authors : E FEATURES;
Page : 249-259
Keywords : Age estimation; eyeball recognition; face detection; wrinkle features;
Abstract
Most of the facial features recognition, say for an example, character, gender and expression has been broadly envisioned. Programmed age assessment and prediction of future expressions have once in a while been examined. With the increase in age of human beings, we can see some gradual changes in their facial features. This paper aims to give a procedure to gauge age gathering that makes use of facial features. This procedure takes account of three stages: 1. Location, 2. Feature Extraction and 3. Classifi cation. The geometric components of face pictures such as face edge, wrinkle topography, left eye to right eye separation, eye to nose separation, eye to jaw separation and eye to lip separation are calculated. By considering the surface and shape data, ag e grouping is done making use of K - Means bunching calculation. Age features are further ordered progressively based on the gathered data making use of K - Means bunching calculation. The acquired results are pretty vast and efficient. This paper can further be utilized for anticipating future confronts, arranging gender orientation, and expression recognition from images of the various faces.
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Last modified: 2017-02-11 20:17:01