E3S Web Conf.
Volume 391, 20234th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
|Number of page(s)
|05 June 2023
A Comprehensive Survey on Face Quality Detection in a Video Frame
1 Department of Computer Science and Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad - 500075
2 Department of Computer Science and Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad - 500075
3 Department of Computer Science and Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad - 500075
4 Department of Computer Science and Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad - 500075
5 Department of Information and Technology, Gokaraju Rangaraju Institute of Technology, Hyderabad - 500090
* Corresponding author: email@example.com
The correctness of the generated face data, which is impacted by a number of variables, significantly affects how well face analysis and recognition systems perform. By automatically analysing the face data quality in terms of its biometric value, it might be able to identify low-quality data and take the necessary action. With a focus on visible wavelength face image input, this study summarises the body of research on the evaluation of face picture quality. The use of DL-based methods is unquestionably expanding, and there are major conceptual differences between them and current approaches, such as the inclusion of quality assessment in face recognition models. In addition to image selection, which is the topic of this article, face picture quality assessment can be used in a wide range of application scenarios. The requirement for comparative algorithm assessments and the difficulty of creating Deep Learning (DL) techniques that are intelligible in addition to providing accurate utility estimates are just a few of the issues and topics that remain unanswered. For each frame, the suggested method is compared to traditional facial feature extraction, and for a collection of video frames, it is compared to well-known clustering algorithms.
Key words: Face quality / video frame / Face detection / Face recognition
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.