Subjective Versus Objective Face Image Quality Evaluation For Face Recognition-Reference-Cited by-同舟云学术

Subjective Versus Objective Face Image Quality Evaluation For Face Recognition

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 3rd International Conference on Biometric Engineering and Applications - ICBEA 2019
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Author:

Khodabakhsh Ali¹,Pedersen Marius¹,Busch Christoph¹

Affiliation:

1. Norwegian University of Science and Technology, Gjøvik, Norway

Publisher

ACM Press

Reference20 articles.

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2. L. Best-Rowden and A. K. Jain. 2018. Learning Face Image Quality From Human Assessments. IEEE Transactions on Information Forensics and Security 13, 12 (Dec 2018), 3064--3077. https://doi.org/10.1109/TIFS.2018.2799585

3. Samarth Bharadwaj, Mayank Vatsa, and Richa Singh. 2014. Biometric quality: a review of fingerprint, iris, and face. EURASIP Journal on Image and Video Processing 2014, 1 (02 Jul 2014), 34. https://doi.org/10.1186/1687-5281-2014-34

4. Jiankang Deng, Jia Guo, and Stefanos Zafeiriou. 2018. Arcface: Additive angular margin loss for deep face recognition. arXiv preprint arXiv: 1801.07698 (2018).

5. W. Funk, M. Arnold, C. Busch, and A. Munde. 2005. Evaluation of image compression algorithms for fingerprint and face recognition systems. In Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop. 72--78. https://doi.org/10.1109/IAW.2005.1495936

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