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12 June 2020 An efficient deep face matching method for ID and selfie photos: SIRFace
Hanh Vu, Thuyen Nguyen Hoang, Nguyen Van Nam
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Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 115191Z (2020) https://doi.org/10.1117/12.2573327
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan
Abstract
User authentication using face biometrics has been becoming popular in many administrative activities (e.g., airport check-in, banking security systems, immigration managements, etc.). In this process, the facial image taken from an authorized document (e.g., identity (ID) card, passport, driving license) is compared to the live face that captured directly by stationary camera or human eyes to check whether they are matched as the same person. The problem is really challenging due to cross-domain difference including age changes, low document quality, and accessories. Recently, a few efforts have been made to build automatic face matching systems based on face recognition technologies. In this paper, we proposed a novel and efficient deep face matching system called SIRFace, which is derived from the RetinaFace detection model, InsightFace embedding model, and SVM classifier. SIRFace also contributed an efficient technique using Cosine similarity to mitigate the impacts of the cross-domain difference, which has not been used in any other related works. The experimental results on a dataset of 2,865 subjects with 9,824 images (i.e., ID and selfie photos) using our method achieved an error rate of 2.34%, which is potentially used for real life applications.
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Hanh Vu, Thuyen Nguyen Hoang, and Nguyen Van Nam "An efficient deep face matching method for ID and selfie photos: SIRFace", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 115191Z (12 June 2020); https://doi.org/10.1117/12.2573327
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KEYWORDS
Facial recognition systems
Image processing
Feature extraction
Cameras
Data modeling
Systems modeling
Digital imaging
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