Journal of Applied Mathematics

An Improved AAM Method for Extracting Human Facial Features

Tao Zhou, Xiao-Jun Wu, Tao Wu, and Zhen-Hua Feng

Full-text: Open access

Abstract

Active appearance model is a statistically parametrical model, which is widely used to extract human facial features and recognition. However, intensity values used in original AAM cannot provide enough information for image texture, which will lead to a larger error or a failure fitting of AAM. In order to overcome these defects and improve the fitting performance of AAM model, an improved texture representation is proposed in this paper. Firstly, translation invariant wavelet transform is performed on face images and then image structure is represented using the measure which is obtained by fusing the low-frequency coefficients with edge intensity. Experimental results show that the improved algorithm can increase the accuracy of the AAM fitting and express more information for structures of edge and texture.

Article information

Source
J. Appl. Math., Volume 2012 (2012), Article ID 643562, 10 pages.

Dates
First available in Project Euclid: 14 December 2012

Permanent link to this document
https://projecteuclid.org/euclid.jam/1355495066

Digital Object Identifier
doi:10.1155/2012/643562

Citation

Zhou, Tao; Wu, Xiao-Jun; Wu, Tao; Feng, Zhen-Hua. An Improved AAM Method for Extracting Human Facial Features. J. Appl. Math. 2012 (2012), Article ID 643562, 10 pages. doi:10.1155/2012/643562. https://projecteuclid.org/euclid.jam/1355495066


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