3D Face Reconstruction and Dynamic Feature Extraction for Pose-Invariant Face Recognition

DOI

10.2991/3ca-13.2013.30How to use a DOI?

Keywords

3D face reconstruction; face recognition; dynamic feature extraction

Abstract

In this paper, we present a pose invariant face recognition framework leveraged on 3D face reconstruction and dynamic feature extraction. First, we synthesize the virtual frontal face from the probe face based on 3D face reconstruction. In the initialization of reconstruction, a tree-structured model is applied to detect landmark points from a 2D image and a hierarchical gaussianization (HG) based method is used for pose estimation. Second, in the recognition step, we present a dynamic feature extraction method to improve the recognizer, which measure the similarity between the synthesized the virtual face and the probe face. Recognition experiments are carried on the Multi-PIE, and CIGIT Face databases. The experimental results show that our system significantly improves the accuracy of face recognition, especially for the faces with extreme poses.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaohu Shao
AU  - Xi Zhou
AU  - Cheng Cheng
AU  - Tony X. Han
PY  - 2013/04
DA  - 2013/04
TI  - 3D Face Reconstruction and Dynamic Feature Extraction for Pose-Invariant Face Recognition
BT  - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation
PB  - Atlantis Press
SP  - 119
EP  - 122
SN  - 1951-6851
UR  - https://doi.org/10.2991/3ca-13.2013.30
DO  - 10.2991/3ca-13.2013.30
ID  - Shao2013/04
ER  -