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Content Provider | IEEE Xplore Digital Library |
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Author | Chuanjun Wang Xuefeng Bai Tiejun Zhang Xiamu Niu |
Copyright Year | 2012 |
Description | Author affiliation: Harbin Institute of Technology Shenzhen Graduate School, 518055 Guangdong China (Chuanjun Wang; Xuefeng Bai; Xiamu Niu) || School of Computer Science and Technology, Harbin Institute of Technology, 150080 China (Tiejun Zhang) |
Abstract | This paper presents a Fourier series based expression deformation model for 3D face recognition. Given a set of training 3D face scans with sufficient facial expressions, these face scans are first preprocessed and represented as a series of Fourier series coefficients. Then, the shape residues between the non-neutral and neutral face scans of the same subject are calculated. These residues are supposed to contain the expression deformation patterns and PCA is applied to learn these patterns. The eigenvector with top eigenvalue in the generated lower dimensional subspace of PCA is then used to build the expression deformation model. Experimental results show the feasibility and merits of the proposed expression deformation model in the recognition scenario. |
Starting Page | 130 |
Ending Page | 133 |
File Size | 276335 |
Page Count | 4 |
File Format | |
ISBN | 9781457721304 |
ISSN | 21579563 |
e-ISBN | 9781457721335 |
DOI | 10.1109/ICNC.2012.6234627 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-05-29 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Deformable models Training Shape Databases Face recognition expression deformation modeling 3D face recognition Face Fourier series PCA |
Content Type | Text |
Resource Type | Article |
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