Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107163
Title: | High-resolution face recognition via deep pore-feature matching | Authors: | Lai, SC Kong, M Lam, KM Li, D |
Issue Date: | 2019 | Source: | In Proceedings of 2019 IEEE International Conference on Image Processing (ICIP), 22-25 September 2019, Taipei, Taiwan, p. 3477-3481 | Abstract: | Because of the advancement of capturing devices, both image resolution and image quality have been significantly improved. Efficiently utilizing facial information is beneficial in enhancing the performance of face recognition methods. For high-resolution face images, pore-scale facial features can be observed. The positions and local patterns of pore features are biologically discriminative, so they can be explored for face identification. In this paper, we extend the previous work on pore-scale features, by proposing a new learning-based descriptor, namely PoreNet. Experiment results show that our proposed descriptor achieves an excellent performance on two high-resolution face datasets, namely Bosphorus and MultiPIE. More importantly, our proposed method significantly outperforms the state-of-the-art Convolutional Neural Network (CNN)-based face recognition method, when query faces are highly occluded. The code of our proposed method is available at: https://github.com/johnnysclai/PoreNet. | Keywords: | Face recognition Feature extraction High-resolution face recognition Pore-scale facial feature |
Publisher: | Institute of Electrical and Electronics Engineers | ISBN: | 978-1-5386-6249-6 (Electronic) 978-1-5386-6250-2 (Print on Demand(PoD)) |
DOI: | 10.1109/ICIP.2019.8803686 | Description: | 2019 IEEE International Conference on Image Processing (ICIP), 22-25 September 2019, Taipei, Taiwan | Rights: | ©2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication S. -C. Lai, M. Kong, K. -M. Lam and D. Li, "High-Resolution Face Recognition Via Deep Pore-Feature Matching," 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 2019, pp. 3477-3481 is available at https://doi.org/10.1109/ICIP.2019.8803686. |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Lai_High-Resolution_Face_Recognition.pdf | Pre-Published version | 964.59 kB | Adobe PDF | View/Open |
Page views
1
Citations as of Jun 30, 2024
SCOPUSTM
Citations
6
Citations as of Jun 21, 2024
WEB OF SCIENCETM
Citations
4
Citations as of Jun 27, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.