Pose-Invariant Face Recognition via RGB-D Images
Joint Authors
Sang, Gaoli
Zhao, Qijun
Li, Jing
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-27
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem.
In this paper, we propose a novel pose-invariant face recognition method via RGB-D images.
By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition.
Texture images in the gallery can be rendered to the same view as the probe via depth.
Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling.
Finally, both texture and depth contribute to the final identity estimation.
Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.
American Psychological Association (APA)
Sang, Gaoli& Li, Jing& Zhao, Qijun. 2015. Pose-Invariant Face Recognition via RGB-D Images. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099660
Modern Language Association (MLA)
Sang, Gaoli…[et al.]. Pose-Invariant Face Recognition via RGB-D Images. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1099660
American Medical Association (AMA)
Sang, Gaoli& Li, Jing& Zhao, Qijun. Pose-Invariant Face Recognition via RGB-D Images. Computational Intelligence and Neuroscience. 2015. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099660
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099660