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Journal of Sensors
Volume 2016 (2016), Article ID 3825931, 10 pages
Research Article

Patch Classifier of Face Shape Outline Using Gray-Value Variance with Bilinear Interpolation

1Department of Embedded Systems Engineering, University of Incheon, Incheon 406-772, Republic of Korea
2TecAce Solutions Inc., Seoul 153-782, Republic of Korea

Received 12 January 2015; Accepted 26 February 2015

Academic Editor: Wei Wu

Copyright © 2016 Seokhoon Kang and Seonwoon Kim. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes a method to classify whether a landmark, which consists of the outline in a face shape model in the shape model based approaches, is properly fitted to feature points. Through this method, the reliability of information can be determined in the process of managing and using the shape. The enlarged face image by image sensor is processed by bilinear interpolation. We use the gray-value variance that considers the texture feature of skin for classification of landmarks. The gray-value variance is calculated in skin area of the patch constructed around the landmark. In order to make a system strong to poses, we project the image of face to the frontal face shape model. And, to fill out each area, the area with insufficient pixel information is filled out with bilinear interpolation. When the fitting is properly done, it has the variance with a low value to be calculated for smooth skin texture. On the other hand, the variance for misaligned landmark shows a high variance by the background and facial contour gradient. We have proposed a classifier using this characteristic and, as a result, classified the true and false in the landmark with an accuracy of 83.32% through the patch classifier.