Sistem Registrasi Dan Identifikasi Wajah Untuk Akses Fasilitas Universitas Kristen Petra Dengan Kombinasi Facenet Dan Hierarchical Navigable Small Worlds
Keywords:
perancangan desain kemasan, minyak esensial, Maharani Kahiyang, kemasan ramah lingkunganAbstract
The Identity Cards of students are used to access the facilities and participate in events of Petra Christian University. The problem which arises from these cards is the misuse by the irresponsible group. For this, the university needs the face identification system as the alternative. This thesis is meant to build a fast, accurate, and easy to use face identification system. The methods used to solve the problem is a combination of Facenet and Hierarchical Navigable Small Worlds (HNSW). Facenet is used to process the face into a 128-dimension vector which will be used for searching. HNSW is a k Nearest Neighbor search method which is used in a large-scale search. Using the method, the system takes an average time of 1 second to identify faces.References
[1] Adjabi, I., Ouahabi, A., Benzaoui, A, & Taleb-Ahmed, A.
(2020). Past, Present, and Future of Face Recognition: A
Review. Electronics, 9 (8), 1188. DOI:
10.3390/electronics9081188.
[2] Aumüller, M., Bernhardsson, E., & Faithfull, A. (2020).
ANN-Benchmarks: A benchmarking tool for approximate
nearest neighbor algorithms. Information Systems, 87,
101374. DOI: 10.1016/j.is.2019.02.006.
[3] Malkov, Y. A. & Yashunin, D. A. (2018). Efficient and robust
approximate nearest neighbor search using hierarchical
navigable small world graphs. IEEE Transactions on Pattern
Analysis and Machine Intelligence, 42 (4), 824-836. DOI:
10.1109/TPAMI.2018.2889473.
[4] Mei, W & Weihong, D. (2021). Deep face recognition: A
survey. Neurocomputing, 429, 215-244. DOI:
10.1016/j.neucom.2020.10.081.
[5] Ranjan, R. et al. (2018). Deep learning for understanding
Faces: machines may be just as good, or better, than humans.
IEEE Signal Processing Magazine, 35 (1), 66-83. DOI:
10.1109/MSP.2017.2764116.
[6] Schroff, F., Kalenichenko, D., Philbin, J. (2015). FaceNet: A
unified embedding for face recognition and clustering. Paper
presented at Proceedings of the 2015 IEEE Conference on
Computer Vision and Pattern Recognition (CVPR), Boston,
MA, USA (pp. 815–823). DOI:
10.1109/CVPR.2015.7298682.
[7] Wen, L. et al. (2019). Approximate nearest neighbor search
on high dimensional data — experiments, analyses, and
improvement. IEEE Transactions on Knowledge and Data
Engineering, 32 (8), 1475 - 1488. DOI:
10.1109/TKDE.2019.2909204.
