Paper Details: Downloads: 908
Serial Number: P1151007997
Title: Novel Method of Adulthood Classification based on Geometrical Features of Face
Authors: M. Chandra Mohan and V. Vijaya Kumar and A. Damodaram
Abstract: Human beings can easily categorize a person’s age group from an image of the person’s face and are often able to be quite precise in this estimation. This ability has not been pursued in the computer vision community. To address this very important area of research, the present paper carried out the task of adulthood classification of a mugshot facial image into a child and adult. The present paper assumes that the features that drastically affect the adulthood classification system are the face geometric properties. Based on this, the present paper proposes a new technique of adulthood classification by extracting feature parameters of face. The feature parameters of the present approach are computed from facial distance features (FDF). From these FDF’s, the various Facial Feature parameters (FFP), and Adulthood Classification Parameters (ACP) are evaluated. The experimental evidence on FGnet aging database and Google Images clearly indicates the significance and accuracy of the proposed classification method.
Keywords: Facial distance features, Facial feature parameters, Adulthood classification parameter
Journal/Conference: International Journal of Graphics, Vision and Image Processing
Volume: 10
Issue: 2
Submission Date: 2/12/2010 12:00:00 AM
Review Date: 3/28/2010 12:00:00 AM
Publishing Date: 5/21/2010 12:00:00 AM
Article Downloads: 908
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