3D Face Reconstruction and Dynamic Feature Extraction for Pose-Invariant Face Recognition
- 10.2991/3ca-13.2013.30How to use a DOI?
- 3D face reconstruction; face recognition; dynamic feature extraction
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.
- © 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/).
Cite this article
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 -