University of Twente Student Theses
Marks Fusion: Development Of Facial Marks Detection System And Fusion With Face Recognition System
Chirca, Lucian (2021) Marks Fusion: Development Of Facial Marks Detection System And Fusion With Face Recognition System.
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| Abstract: | Facial marks like freckles, moles, scars, pockmarks have been used in the past to identify individuals. There have been developed systems integrating both Facial Marks de- tection with Facial Recognition [17] [2], which showed im- proved performance over only using Facial Recognition. These systems used classic blob detection approaches like LoG (Laplacian of Gaussian) or Fast Radial Symmetry Transform for detecting facial marks, which gave a lot of False Positives, or had people manually annotate fa- cial marks, which is too time consuming. Although there have been significant improvements in detecting Facial Marks using a Convolutional Neural Network, a system integrating this new approach with facial detection has not been implemented yet. This paper improves the state- of-the art in Facial Marks detection by using CNNs with deeper architectures and shows that a system combining a state-of-the-art algorithm in Facial Recognition with a Fa- cial Marks Systems outperforms one that only uses Facial Recognition, especially in the case of monozygotic twins. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/85680 |
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