Haoting, L, Na, Z, Wang, Y et al. (4 more authors) (2021) Development of a face recognition system and its intelligent lighting compensation method for dark-field application. IEEE Transactions on Instrumentation and Measurement. ISSN 0018-9456
Abstract
A face recognition system which uses 3D lighting estimation and optimal lighting compensation for dark-field application is proposed. To develop the proposed system, which can realize people identification in a near scene dark-field environment, a light-emitting diode (LED) overhead light, eight LED wall lights, a visible light binocular camera, and a control circuit are used. First, 68 facial landmarks are detected and their coordinates in both image as well as camera coordinate systems are computed. Second, a 3D morphable model (3DMM) is developed after considering facial shadows, and a transformation matrix between the 3DMM and camera coordinate systems is estimated. Third, to assess lighting uniformity, 30 evaluation points are selected from the face. Sequencing computations of LED radiation intensity, ray reflection luminance, camera response, and face lighting uniformity are then carried out. Ray occlusion is processed using a simplified 3D face model. Fourth, an optimal lighting compensation is realized: the overhead light is used for flood lighting, and the wall lights are employed as meticulous lighting. A genetic algorithm then is used to identify the optimal lighting of the wall lights. Finally, an Eigenface method is used for face recognition. The results show that our system and method can improve face recognition accuracy by >10% compared to traditional recognition methods.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 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. |
Keywords: | face recognition , distributed intelligent lighting , 3DMM , light compensation , dark-field environment |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Sep 2021 09:36 |
Last Modified: | 10 Sep 2021 09:36 |
Status: | Published online |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/TIM.2021.3111076 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177925 |