دورية أكاديمية
Analysis of Real-Time Face-Verification Methods for Surveillance Applications
| العنوان: | Analysis of Real-Time Face-Verification Methods for Surveillance Applications |
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| المؤلفون: | Filiberto Perez-Montes, Jesus Olivares-Mercado, Gabriel Sanchez-Perez, Gibran Benitez-Garcia, Lidia Prudente-Tixteco, Osvaldo Lopez-Garcia |
| المصدر: | Journal of Imaging, Vol 9, Iss 2, p 21 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Electronic computers. Computer science |
| مصطلحات موضوعية: | face verification, lightweight face recognition, video surveillance, MobileFaceNet, EfficientNet, GhostNet, Photography, TR1-1050, Computer applications to medicine. Medical informatics, R858-859.7, Electronic computers. Computer science, QA75.5-76.95 |
| الوصف: | In the last decade, face-recognition and -verification methods based on deep learning have increasingly used deeper and more complex architectures to obtain state-of-the-art (SOTA) accuracy. Hence, these architectures are limited to powerful devices that can handle heavy computational resources. Conversely, lightweight and efficient methods have recently been proposed to achieve real-time performance on limited devices and embedded systems. However, real-time face-verification methods struggle with problems usually solved by their heavy counterparts—for example, illumination changes, occlusions, face rotation, and distance to the subject. These challenges are strongly related to surveillance applications that deal with low-resolution face images under unconstrained conditions. Therefore, this paper compares three SOTA real-time face-verification methods for coping with specific problems in surveillance applications. To this end, we created an evaluation subset from two available datasets consisting of 3000 face images presenting face rotation and low-resolution problems. We defined five groups of face rotation with five levels of resolutions that can appear in common surveillance scenarios. With our evaluation subset, we methodically evaluated the face-verification accuracy of MobileFaceNet, EfficientNet-B0, and GhostNet. Furthermore, we also evaluated them with conventional datasets, such as Cross-Pose LFW and QMUL-SurvFace. When examining the experimental results of the three mentioned datasets, we found that EfficientNet-B0 could deal with both surveillance problems, but MobileFaceNet was better at handling extreme face rotation over 80 degrees. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2313-433X |
| Relation: | https://www.mdpi.com/2313-433X/9/2/21; https://doaj.org/toc/2313-433X |
| DOI: | 10.3390/jimaging9020021 |
| URL الوصول: | https://doaj.org/article/359c091212754b2c94abab98aee5e1a5 |
| رقم الأكسشن: | edsdoj.359c091212754b2c94abab98aee5e1a5 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 2313433X |
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| DOI: | 10.3390/jimaging9020021 |