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Unconstrained Face Identification Based on 3D Face Frontalization and Support Vector Guided Dictionary Learning by Zhi Zhang; Xin Xu; Jiuzhen Liang; Bingyu Sun is a Engineering article available to read on EtoBox.

What is Unconstrained Face Identification Based on 3D Face Frontalization and Support Vector Guided Dictionary Learning about?

Face identification aims at putting a label on an unknown face with respect to some training set. Unconstrained face identification is a challenging problem because of the possible variations in face pose, illumination, occlusion, and facial expression. This paper presents an unconstrained face identification method based on face frontalization and learning-based data representation. Firstly, the frontal views of unconstrained face images are automatically generated by using a single, unchanged 3D face model. Then, we crop the face relevant regions of the frontal views to segment faces from the backgrounds. At last, to enhance the discriminative capability of the coding vectors, a support vector-guided dictionary learning (SVGDL) model is applied to adaptively assign different weights to different pairs of coding vectors. The performance of the proposed method FSVGDL (frontalization-based support vector guided dictionary learning) is evaluated on the Labeled Faces in the wild (LFW) database. After decision fusion, the identification accuracy yields 97.17% when using 7 images per individual for training and 3 images per individual for testing with 158 classes in total.

Who reads Unconstrained Face Identification Based on 3D Face Frontalization and Support Vector Guided Dictionary Learning?

Author

Zhi Zhang; Xin Xu; Jiuzhen Liang; Bingyu Sun

Publisher

Hindawi Publishing Corporation; Hindawi Limited; Lausanne: Gordon and Breach Science Publishers SA, 1995-; London: Hindawi (ISSN 1024-123X)

Published

2020

Language

EN

Field

Engineering (Physical Sciences)