Bappaditya Mandal b.mandal@keele.ac.uk
Face recognition: Perspectives from the real world
Mandal, Bappaditya
Authors
Abstract
In this paper, we analyze some of our real-world deployment of face recognition (FR) systems for various applications and discuss the gaps between expectations of the user and what the system can deliver. We evaluate some of the existing algorithms with modifications for applications including FR on wearable devices (like Google Glass) for improving social interactions, monitoring of elderly people in senior citizens centers, FR of children in child care centers and face matching between a scanned IC/passport face image and few live webcam images for automatic hotel/resort checkout or clearance. Each of these applications poses unique challenges and demands specific research components so as to adapt in the actual sites.
Citation
Mandal, B. (2016). Face recognition: Perspectives from the real world. . https://doi.org/10.1109/icarcv.2016.7838675
Conference Name | 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV) |
---|---|
Conference Location | Phuket, Thailand |
Start Date | Nov 13, 2016 |
End Date | Nov 15, 2016 |
Publication Date | 2016-11 |
Deposit Date | Nov 17, 2023 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
DOI | https://doi.org/10.1109/icarcv.2016.7838675 |
Publisher URL | https://ieeexplore.ieee.org/document/7838675 |
You might also like
Deep Neural Network Based Attention Model for Structural Component Recognition
(2023)
Conference Proceeding
StructureNet: Deep Context Attention Learning for Structural Component Recognition
(2022)
Conference Proceeding
Variance-guided attention-based twin deep network for cross-spectral periocular recognition
(2020)
Journal Article
Multi-Deformation Aware Attention Learning for Concrete Structural Defect Classification
(2020)
Journal Article
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search