The article is dedicated to the investigation of face identification methods and aims to determine the most suitable one for a security system based on facial recognition from surveillance cameras. The time costs of these methods and their robustness against geometric scale distortions and rotations in various planes have been analyzed. Custom datasets have been generated for experimentation purposes. Special attention has been given to striking a balance between the speed and accuracy of the examined methods for their utilization as the initial stage of a security system based on facial recognition in a video stream. The conducted research has revealed that the most effective methods are RetinaFace-MobileNet0.25, FaceBoxes, SCRFD500MF, and CenterFace; RetinaFaceResNet125, DSFD, and RetinaFaceMobile0.25 which are resilient to facial rotations. Furthermore, when selecting the most optimal facial recognition method for application within a security system, the presence of informative facial parameters was taken into account, as well as the fact that the recognition methods used in the subsequent stage have their limitations concerning resilience to affine transformations.
[1] Zhang, K., Zhang, Z., Li, Z., & Qiao, Y. (2016). Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Processing Letters, 23(10), 1499–1503. doi : 10.1109/lsp.2016.2603342.
[2] Zhang, S., Zhu, X., Lei, Z., Shi, H., Wang, X., & Li, S. Z. (2017). FaceBoxes: A CPU real-time face detector with high accuracy. 2017 IEEE International Joint Conference on Biometrics (IJCB). doi : 10.1109/btas.2017.8272675.
[3] Ren, S., He, K., Girshick, R., & Sun, J. (2017). Faster R-CNN: Towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(6), 1137–1149. https://doi.org/10.1109/tpami.2016.2577031.
[4] Deng, J., Guo, J., Ververas, E., Kotsia, I., & Zafeiriou, S. (2020). Retinaface: Single-shot multilevel face localisation in the wild. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr42600.2020.00525
[5] Xu, Y., Yan, W., Yang, G., Luo, J., Li, T., & He, J. (2020). Centerface: Joint face detection and alignment using face as point. Scientific Programming, 2020, 1–8. https://doi.org/10.1155/2020/7845384
[6] Guo, J., Deng, J., Lattas, A., & Zafeiriou, S. (2021, May 10). Sample and computation redistribution for efficient face detection. arXiv.org. Retrieved July 15, 2023, from https://arxiv.org/abs/2105.04714
[7] Zhang, E., & Zhang, Y. (2009). Average precision. Encyclopedia of Database Systems, 192–193. https://doi.org/10.1007/978-0-387-39940-9_482
[8] Deepinsight. (n.d.). Insightface/model_zoo at master • deepinsight/insightface. GitHub. Retrieved July 15, 2023, from https://github.com/deepinsight/insightface/tree/master/model_zoo
[9] Yang, S., Luo, P., Loy, C. C., & Tang, X. (2016). Wider face: A face detection benchmark. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2016.596
[10] Timesler. (n.d.). Timesler/facenet-pytorch: Pretrained Pytorch Face Detection (MTCNN) and facial recognition (InceptionResnet) models. GitHub. Retrieved July 15, 2023, from https://github.com/timesler/facenet-pytorch
[11] Zisianw. (n.d.). Zisianw/faceboxes.pytorch: A pytorch implementation of faceboxes. GitHub. Retrieved July 15, 2023, from https://github.com/zisianw/FaceBoxes.PyTorch
[12] Hukkelas. (n.d.). Hukkelas/DSFD-pytorch-inference: A high-performance pytorch implementation of face detection models, including RetinaFace and DSFD. GitHub. Retrieved July 15, 2023, from https://github.com/hukkelas/DSFD-Pytorch-Inference
[13] Star-Clouds. (n.d.). Star-Clouds/Centerface: Face detection. GitHub. Retrieved July 15, 2023, from https://github.com/Star-Clouds/CenterFace
[14] Deepinsight. (n.d.). Insightface/python-package at master • deepinsight/insightface. GitHub. Retrieved July 15, 2023, from https://github.com/deepinsight/insightface/tree/master/pythonpackage
[15] Unique, worry-free model photos. Generated Photos. (n.d.). Retrieved July 15, 2023, from https://generated.photos/
[16] Character Creator (CC) is a full character creation solution for designers to easily generate, import and customize stylized or realistic character. Retrieved July 10, 2023, from https://www.reallusion.com/character-creator/
[17] Olena Yakovleva, Andrii Kovtunenko, Valentyn Liubchenko, Vadym Honcharenkoand Oleg Kobylin Face Detection for Video Surveillance-based Security System COLINS-2023: 7th International Conference on Computational Linguistics and Intelligent Systems, April 20-21, 2023, Kharkiv, Ukraine p.69-86